Francesc Serratosa. List of Publications
https://webs-deim.urv.cat/~francesc.serratosa/
DBLP ResearchGate Google Scholar
(Red: In Science Citation Index)
The ultimate aims of
research are to generate measurable and testable data, gradually adding to the
accumulation of human knowledge
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180 (58). A. Fernández, N. Segura-Alabart and F. Serratosa, The MultiFurcating Neighbor-Joining Algorithm for Reconstructing Polytomic Phylogenetic Trees, Journal of Molecular Evolution, https://doi.org/10.1007/s00239-023-10134-z, 2023.
179. F.
Serratosa, Graph Embedding
of almost constant large graphs, Iberoamerican Congress on Pattern Recognition 2023, Coimbra,
Portugal, LNCS: 14469, pp: 16–30, 2023. https://link.springer.com/chapter/10.1007/978-3-031-49018-7_2
178. S.
Fadlallah, N. Segura-Alabart, C. Julià and F. Serratosa, Splitting Structural and Semantic Knowledge in Graph
Autoencoders for Graph Regression, Graph-Based Representations in Pattern Recognition 2023, Salerno, Italy,
LNCS: 14121, pp: 81-91, 2023. https://doi.org/10.1007/978-3-031-42795-4_8
177. A.
Qadir, W. González-López, N. Duncan and
F. Serratosa, Automatic fish detection and tracking for analysis of
reproductive behaviours in Senegalese sole (Solea senegalensis) using neural
networks and the DeepSORT algorithm, 12th International Symposium on
Reproductive Physiology of Fish 2023, Crete, Grece, 2023.
176 (57). S. Fadlallah,
C. Julià, S. García-Vallvé, G. Pujadas and F. Serratosa, Drug Potency Prediction of SARS-CoV-2 Main Protease
Inhibitors Based on a Graph Generative Model, International
Journal of Molecular Sciences, pp:, 2023. https://www.mdpi.com/1422-0067/24/10/8779
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175. W.A
González López, A. Qadir1, N. Duncan and F. Serratosa, Fish tracking for
automatic detection of reproductive behaviour, Aquaculture Europe 2022,
Rimini, Italy, pp:, 2022.
174. S.
Fadlallah, C. Julià & F.
Serratosa, Graph Regression based on Graph Autoencoders, Syntactic and
Structural Pattern Recognition, SSPR2022, LNCS 13813, pp 142:151, 2022. https://doi.org/10.1007/978-3-031-23028-8_15
173. E.
Rica, S.Álvarez & F. Serratosa, Tarragona Graph Database for Machine
Learning based on Graphs, Syntactic and Structural Pattern Recognition, SSPR2022,
LNCS 13813, pp 302:310, 2022. https://doi.org/10.1007/978-3-031-23028-8_31
172. E.
Rica, S.Álvarez & F. Serratosa, Learning Distances between Graph nodes and
edges, Syntactic and Structural Pattern Recognition, SSPR2022, LNCS
13813, pp 103:112, 2022. https://doi.org/10.1007/978-3-031-23028-8_11
171. E.
Rica, S.Álvarez & F. Serratosa, Zero-Error Digitisation and
Contextualisation of Piping and Instrumentation Diagrams using Node
Classification and Sub-graph Search, Syntactic and Structural Pattern
Recognition, SSPR2022, LNCS 13813, pp. 274:282, 2022. https://doi.org/10.1007/978-3-031-23028-8_28
170 (56). N.
Segura-Alabart, F. Serratosa, S. Gómez1 and A. Fernández, Non-unique UPGMA
clusterings of microsatellite markers, Briefings in Bioinformatics,
2022. https://doi.org/10.1093/bib/bbac312
169. F.
Serratosa, S. Álvarez, L. Escorihuela and M. Calatayud, Subgraph
NanoFingerprint for modelling metal oxide nanoparticles based on connected
atoms exploration. NanoWeek & NanoCommons Final Conference 2022,
Cyprus 2022.
168 (55). Y. Aybars, B.
Martorell, F. Serratosa, N. Aguilera-Porta, M. Calatayud, Analysing the TiO2
surface reactivity based on oxygen vacancies computed by DFT and DFTB methods, Journal
of Physics: Condensed Matter 34, 2022. https://iopscience.iop.org/article/10.1088/1361-648X/ac7025
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167 (54). E. Rica, S.
Álvarez and F. Serratosa, Ligand-Based Virtual Screening based on The Graph
Edit Distance, International Journal of Molecular Sciences, 22, 12751,
2021. https://doi.org/10.3390/ijms222312751
166 (53). F. Serratosa,
Redefining the Graph Edit Distance, S. N. Computer Science, 2:438, 2021.
https://doi.org/10.1007/s42979-021-00792-5
165 (52). E. Rica, S.
Álvarez and F. Serratosa, Group of Components Detection in Engineering Drawings
based on Graph Matching, Engineering Applications of Artificial Intelligence,
104, 2021.
164. Y.
Çetin, B. Martorell and F. Serratosa, New descriptors in toxicology prediction
of nanomaterials: Using quasi-ab initio MD simulations for the estimation of
aqueous ZnO and TiO2 surface structure parameters, Nanotox2021, 2021.
163 (51). E. Rica, S. Álvarez
and F. Serratosa, On-line learning the graph edit distance costs, Pattern
Recognition Letters, 146, pp:52-62, 2021.
----2020----
162. J.
Contreras-García, F. Serratosa, S. Gómez, H. Y. Geng, G. J. Ackland & M.
Marqués, Predicting chemical bond at high pressure with machine learning, 58th
European High Pressure Research Group International Conference, Tenerife,
Spain, EHPRG 2020, 2020.
161. P.
Santacruz and F. Serratosa, Incorporating a graph-matching algorithm into a
muscle mechanics model, International Conference on Pattern Recognition, pp: 53
– 58, ICPR2020, 2021.
160. S.
Algabli and F. Serratosa, Learning Graph Matching Substitution Weights based on
a Linear Regression, International Conference on Pattern Recognition, pp: 39 –
46, ICPR2020, 2021.
159 (50). D. Conte, F.
Serratosa, Interactive Online Learning for Graph Matching using Active
Strategies, Knowledge Based Systems, 105, 106275, 2020. https://doi.org/10.1016/j.knosys.2020.106275
158 (49). F. Serratosa, A
general model to define the substitution, insertion and deletion graph edit
costs based on an embedded space, Pattern Recognition Letters, 138, pp:
115-122, 2020. https://doi.org/10.1016/j.patrec.2020.07.010
157 (48). P. Santacruz and F. Serratosa, Error-tolerant graph matching in linear computational cost using an initial small partial matching, Pattern Recognition Letters, 134, pp:10-19 2020. https://www.sciencedirect.com/science/article/pii/S0167865518301235
156 (47). C.
Garcia-Hernandez, A. Fernández and F Serratosa, Learning the Edit Costs of the
Graph Edit Distance Applied to Ligand-Based Virtual Screening, Current
Topics in Medicinal Chemistry, 20, pp: 1-11, 2020, https://doi.org/10.2174/1568026620666200603122000
155 (46). Yasin, Haque,
Adnan, Rahnuma, Hossain, Naha, Kabir and Serratosa, Localization of Autonomous
Robot in an Urban Area Based on SURF Feature Extraction of Images, International
Journal of Technology Diffusion, 11 (4), 2020. https://doi.org/10.4018/IJTD.20201001
154. C.
Garcia-Hernandez, A. Fernandez and F. Serratosa, Training a molecular
dissimilarity measure for target specific activities, Society of Environmental
Toxicology and Chemistry, SETAC 2020, Dublin, Ireland, 2020.
153 (45). E. Rica, C.
Moreno-Garcia, S. Alvarez, F. Serratosa, Reducing Human Effort in Engineering
Drawing Validation, Computers in Industry 117, pp: 103198, 2020. https://doi.org/10.1016/j.compind.2020.103198
152 (44). P. Santacruz
& F. Serratosa, Learning the graph edit costs based on a learning model
applied to sub-optimal graph matching, Neural Processing Letters, 51,
pp: 881–904, 2020. https://link.springer.com/article/10.1007/s11063-019-10121-w
151 (43). F. Serratosa, A
commentary on “Learning error-correcting graph matching with a multiclass
neural network”, Pattern Recognition Letters, 129, pp:16-18, 2020. https://doi.org/10.1016/j.patrec.2019.10.033
150 (42). C. Moreno-García, F. Serratosa & X. Jiang, Correspondence edit distance to obtain a set of weighted means of graph correspondences, Pattern Recognition Letters, 134 pp: 29-36, 2020. https://doi.org/10.1016/j.patrec.2018.08.027
----2019----
149 (41). Junchi Yan,
Minsu Cho, Francesc Serratosa, Gui-Song Xia, Yinqiang Zheng, Editorial. Pattern
Recognition Letters, 127 pp:1-2, 2019. https://doi.org/10.1016/j.patrec.2019.03.005
148. S.
Algabli, P. Santacruz & F. Serratosa, Learning the Graph Edit Distance
Parameters for Point-Set Image Registration, International Conference on
Computer Analysis of Images and Patterns, CAIP 2019, Salerno, Italy,
LNCS 11678, pp: 447-456, 2019. https://doi.org/10.1007/978-3-030-29888-3_36
147 (40). C.
Moreno-García and F. Serratosa, Generalised Median of Graph Correspondences, Pattern
Recognition Letters, 125, pp: 389-395, 2019. https://doi.org/10.1016/j.patrec.2019.05.015
146 (39). C.
Garcia-Hernandez, A. Fernandez and F. Serratosa, Ligand-Based Virtual Screening
Using Graph Edit Distance as Molecular Similarity Measure, Journal of
Chemical Information and Modelling, 59 (4), pp: 1410-1421, 2019. https://doi.org/10.1021/acs.jcim.8b00820
145. X. Cortés, D. Conte & F. Serratosa, Sub-optimal Graph Matching by Node-to-node Assignment Classification, Graph based Representations in Pattern Recognition, GbRPR 2019, Tours, France, LNCS 11510, pp: 35–44, 2019.
144. E.
Rica, S. Álvarez & F. Serratosa, On-line Learning
the Edit Costs based on an Embedded model , Graph based Representations in
Pattern Recognition, GbRPR 2019, Tours, France, LNCS 11510, pp: 121–130,
2019.
143. E.
Rica, S. Álvarez & F. Serratosa, Learning the
Graph edit costs: What do we want to optimise? , Graph based Representations in
Pattern Recognition, GbRPR 2019, Tours, France, LNCS 11510, pp: 25–34,
2019.
142. C.
García-Hernandez, A. Fernández & F. Serratosa, Graph edit distance as
molecular similarity measure for virtual screening, Graph based Representations
in Pattern Recognition, SETAC 2019, Helsinki, Finland, 2019.
141 (38). F. Serratosa,
Graph edit distance: Restrictions to be a metric, Pattern Recognition,
90, pp: 250-256, 2019. https://doi.org/10.1016/j.patcog.2019.01.043
----2018----
140 (37). S. Algabli
& F. Serratosa, Embedding the node-to-node mappings to learn the Graph edit
distance parameters, Pattern Recognition Letters, 112, pp: 353-360,
2018. https://doi.org/10.1016/j.patrec.2018.08.026
139. X.
Cortés, D. Conte, H. Cardot & F. Serratosa, A Deep Neural Network
Architecture to Estimate Node Assignment Costs for the Graph Edit Distance,
Syntactic and Structural Pattern Recognition, SSPR2018, LNCS 11004, pp:
326-336, 2018. https://doi.org/10.1007/978-3-319-97785-0_31
138. P.
Santacruz & F. Serratosa, Learning the Sub-optimal Graph Edit Distance edit
costs based on an embedded model, Syntactic and Structural Pattern Recognition,
SSPR2018, LNCS 11004, pp: 282-292, 2018. https://doi.org/10.1007/978-3-319-97785-0_27
137. C.
Moreno-García & F. Serratosa, Modelling the Generalised Median
Correspondence through an Edit Distance, Syntactic and Structural Pattern
Recognition, SSPR2018, LNCS 11004, pp: 271-281, 2018. https://doi.org/10.1007/978-3-319-97785-0_26
136. P.
Santacruz & F. Serratosa, Graph Edit Distance Testing through Synthetic
Graphs Generation, International Conference on Pattern Recognition, ICPR2018,
pp: 572-577, 2018.
135 (36). F. Serratosa, A
methodology to generate attributed graphs with a bounded graph edit distance
for graph-matching testing, International Journal of Pattern Recognition and
Artificial Intelligence, 32 (11), pp: 1850038 (19 pages), 2018. https://doi.org/10.1142/S0218001418500386
----2017----
134. P. Santacruz, S. Algabli & F. Serratosa, Node matching computation between two large graphs in linear computational cost, Graph based Representations in Pattern Recognition, GbRPR 2017, Capri, Italy, LNCS 10310, pp: 143–153, 2017. http://dx.doi.org/10.1007/978-3-319-58961-9_13
133. C. Moreno-García, F. Serratosa & X. Jiang, An Edit Distance between Graph Correspondences, Graph based Representations in Pattern Recognition, GbRPR 2017, Capri, Italy, LNCS 10310, pp: 232–241, 2017. https://doi.org/10.1007/978-3-319-58961-9_21
132 (35). C. Moreno-García & F. Serratosa, Obtaining the Consensus of Multiple Correspondences between Graphs through Online Learning, Pattern Recognition Letters, 87, pp: 79-86, 2017. http://dx.doi.org/10.1016/j.patrec.2016.09.003
131 (34). C. Moreno-García & F. Serratosa, Correspondence Consensus of Two Sets of Correspondences through Optimisation Functions, Pattern Analysis and Applications, 20(1), pp: 201-213, 2017. http://dx.doi.org/10.1007/s10044-015-0486-y
----2016----
130. F. Serratosa, X. Cortés & K. Riesen, On the Relevance of Local Neighbourhoods for Greedy Graph Edit Distance, Syntactic and Structural Pattern Recognition, SSPR2016, LNCS 10029, pp. 121-131, Merida, Mexico, 2016. http://dx.doi.org/10.1007/978-3-319-49055-7_11
129. C. Moreno-García, F. Serratosa & X. Cortés, Generalised Median of a Set of Correspondences based on the Hamming Distance, Syntactic and Structural Pattern Recognition, SSPR2016, LNCS 10029, pp: 507-518, Merida, Mexico, 2016. http://dx.doi.org/10.1007/978-3-319-49055-7_45
128. C. Moreno-García, X. Cortés & F. Serratosa, A Graph Repository for Learning Error-Tolerant Graph Matching, Syntactic and Structural Pattern Recognition, SSPR2016, LNCS 10029, pp: 519-529, Merida, Mexico, 2016. http://dx.doi.org/10.1007/978-3-319-49055-7_46
127. F. Serratosa, X. Cortés & C. Moreno-García, Graph Edit Distance or Graph Edit Pseudo-Distance?, Syntactic and Structural Pattern Recognition, SSPR2016, LNCS 10029, pp: 530–540, Merida, Mexico, 2016. http://dx.doi.org/10.1007/978-3-319-49055-7_47
126 X. Cortés, F. Serratosa & C. Moreno-García, Semi-automatic pose estimation of a fleet of robots with embedded stereoscopic cameras, IEEE International Conference on Emerging Technologies and Factory Automation, ETFA2016, pp: 1-6, 2016. http://dx.doi.org/10.1109/ETFA.2016.7733640
125 G. Manzo, F. Serratosa & M. Vento, Interactive pose calibration of a set of cameras for video surveillance, IEEE International Conference on Emerging Technologies and Factory Automation, ETFA2016, pp: 1-4, 2016. http://dx.doi.org/10.1109/ETFA.2016.7733663
124 (33) G. Manzo, F. Serratosa & M. Vento, Online Human Assisted and Cooperative Pose Estimation of 2D-cameras, Expert Systems With Applications, 60, pp: 258-268, 2016. http://dx.doi.org/10.1016/j.eswa.2016.05.012
123 C. Moreno-García, M. Aceves-Martins & F. Serratosa, Unsupervised Machine Learning Application to Perform a Systematic Review and Meta-Analysis in Medical Research, Computación y Sistemas, 20(1), pp: 7-17, 2016. http://dx.doi.org/10.13053/CyS-20-1-2360
122 (32) G. Sanroma, A Penate-Sanchez, R. Alquezar, F. Serratosa, F. Moreno-Noguer, J. Andrade-Cetto & M.A. Gonzalez, MSClique: Multiple Structure Discovery through the Maximum Weighted Clique Problem, PLOS ONE, 2016. http://dx.doi.org/10.1371/journal.pone.0145846
121 (31) X. Cortés & F. Serratosa, Cooperative Pose Estimation of a Fleet of Robots based on Interactive Points Alignment, Expert Systems With Applications, 45, pp: 150-160, 2016. http://dx.doi.org/10.1016/j.eswa.2015.09.049
120 (30) X. Cortés & F. Serratosa, Learning Graph Matching Substitution Weights based on the Ground Truth Node Correspondence, International Journal of Pattern Recognition and Artificial Intelligence, 30(2), pp: 1650005 [22 pages], 2016. http://dx.doi.org/10.1142/S0218001416500051
119 (29) C. Moreno-García & F. Serratosa, Consensus of Multiple Correspondences to increase the accuracy in Image Registration, Computer Vision and Image Understanding, 142, pp: 50-64, 2016. http://dx.doi.org/10.1016/j.cviu.2015.08.008
----2015----
118 (28) C. Moreno-García & F. Serratosa, Online Learning the Consensus of Multiple Correspondences Between Sets, Knowledge based Systems, 90, pp: 49-57, 2015. http://dx.doi.org/10.1016/j.knosys.2015.09.034
Corrigendum: http://deim.urv.cat/~francesc.serratosa/2015_Moreno_Serratosa_KBS_Corrigendum.pdf
117 (27) F. Serratosa & X. Cortés, Graph Edit Distance: moving from global to local structure to solve the graph-matching problem, Pattern Recognition Letters, 65, pp: 204-210, 2015. http://dx.doi.org/10.1016/j.patrec.2015.08.003
116 (26). M. Ferrer, F. Serratosa & K. Riesen, Improving Bipartite Graph Matching by Assessing the Assignment Confidence, Pattern Recognition Letters, 65, pp: 29-36, 2015. http://dx.doi.org/10.1016/j.patrec.2015.07.010
115 (25). F. Serratosa, Computation of Graph Edit Distance: Reasoning about Optimality and Speed-up, Image and Vision Computing, 40, pp: 38-48, 2015. http://dx.doi.org/10.1016/j.imavis.2015.06.005
114. X. Cortés, F. Serratosa & C. Moreno-García, Ground truth Correspondence between nodes to Learn Graph-Matching Edit-Costs, Computer Analysis of Images and Patterns, CAIP 2015, Valletta, Malta, LNCS 9256, pp: 113-124, 2015. http://dx.doi.org/10.1007/978-3-319-23192-1_10
113. M. Ferrer, F. Serratosa & K. Riesen, Learning Heuristics to Reduce the Overestimation of Bipartite Graph Edit Distance Approximation, International Conference on Machine Learning and Data Mining, MLDM 2015, LNAI 9166, pp: 17-31, Hamburg, Germany, 2015. (Best Paper Award). http://dx.doi.org/10.1007/978-3-319-21024-7_2
112. X. Cortés, F. Serratosa & C. Moreno-García, On the Influence of Node Centralities on Graph Edit Distance for Graph Classification, Graph based Representations in Pattern Recognition, GbRPR 2015, Beijing, China, LNCS 9069, pp: 231-241, 2015. http://dx.doi.org/10.1007/978-3-319-18224-7_23
111. M. Ferrer, F. Serratosa & K. Riesen, A First Step Towards Exact Graph Edit Distance Using Bipartite Graph Matching, Graph based Representations in Pattern Recognition, GbRPR 2015, Beijing, China, LNCS 9069, pp: 77-86, 2015. http://dx.doi.org/10.1007/978-3-319-18224-7_8
110. C. Moreno-García, F. Serratosa & X. Cortés, Consensus of Two Graph Correspondences through a Generalisation of the Bipartite Graph Matching Algorithm, Graph based Representations in Pattern Recognition, GbRPR 2015, Beijing, China, LNCS 9069, pp: 87-97, 2015. http://dx.doi.org/10.1007/978-3-319-18224-7_9
109. C. Moreno-García, X. Cortés & F. Serratosa, Iterative Versus Voting Method to Reach Consensus Given Multiple Correspondences of Two Sets, Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2015, Santiago de Compostela, Spain, LNCS 9117, pp: 530-540, 2015.
108 (24). X. Cortés & F. Serratosa, Learning Graph-Matching Edit-Costs based on the Optimality of the Oracle's Node Correspondences, Pattern Recognition Letters, 56, pp: 22 - 29, 2015. http://dx.doi.org/10.1016/j.patrec.2015.01.009
107 (23). F. Serratosa, Speeding up Fast Bipartite Graph Matching trough a new cost matrix, International Journal of Pattern Recognition and Artificial Intelligence, 29 (2), 1550010, [17 pages] 2015. http://dx.doi.org/10.1142/S021800141550010X
106 (22). F. Serratosa & X. Cortés, Interactive Graph-Matching using Active Query Strategies, Pattern Recognition 48 (4), pp: 1364-1373, 2015. http://dx.doi.org/10.1016/j.patcog.2014.10.033
105. X. Cortés, F. Serratosa & C. Moreno-García, An Interactive Model for Structural Pattern Recognition based on the Bayes Classifier, International Conference on Pattern Recognition Applications and Methods, ICPRAM 2015, Lisbon, Portugal, pp: 240-247, 2015. http://dx.doi.org/10.5220/0005201602400247
104 (21). X. Cortés & F. Serratosa, An Interactive Method for the Image Alignment problem based on Partially Supervised Correspondence, Expert Systems With Applications 42 (1), pp: 179 - 192, 2015. http://dx.doi.org/10.1016/j.eswa.2014.07.051
----2014----
103. C. Moreno-García & F. Serratosa, Fast and Efficient Palmprint Identification of a Small Sample within a Full Image, Computación y Sistemas, 18 (4), pp: 683–691, 2014. http://dx.doi.org/10.13053/CyS-18-4-2059
102. X. Cortés, C. Moreno-García & F. Serratosa, Learning Graph-Matching Substitution Costs based on the Optimality of the Oracle’s Correspondence, Iberoamerican Congress on Pattern Recognition, CIARP2014, LNCS 8827, pp: 506–514, Puerto Vallarta, Mexico, 2014. http://dx.doi.org/10.1007/978-3-319-12568-8_62
101. C. Moreno-García, X. Cortés & F. Serratosa, Partial to Full Image Registration based on Candidate Positions and Multiple Correspondences, Iberoamerican Congress on Pattern Recognition, CIARP2014, LNCS 8827, pp: 745–753, Puerto Vallarta, Mexico, 2014. http://dx.doi.org/10.1007/978-3-319-12568-8_90
100. F. Serratosa & X. Cortés, Human Interaction to Improve the Image Alignment on a Cooperative Robotic Framework, IEEE International Conference on Emerging Technologies and Factory Automation, ETFA2014, PD-001198, Barcelona, Spain, 2014. http://dx.doi.org/10.1109/ETFA.2014.7005104
99. C. Moreno-García & F. Serratosa, Weighted Mean Assignment of a Pair of Correspondences using Optimisation functions, Syntactic and Structural Pattern Recognition, SSPR2014, LNCS 8621, pp: 301-311, Joensuu, Finland, 2014. http://dx.doi.org/10.1007/978-3-662-44415-3_31
98. F. Serratosa & X. Cortés, Edit Distance computed by Fast Bipartite Graph Matching, Syntactic and Structural Pattern Recognition, SSPR2014, LNCS 8621, pp: 253-262, Joensuu, Finland, 2014. http://dx.doi.org/10.1007/978-3-662-44415-3_26
97 (20). F. Serratosa, Fast Computation of Bipartite Graph Matching, Pattern Recognition Letters 45, pp: 244 - 250, 2014. http://dx.doi.org/10.1016/j.patrec.2014.04.015
Corrigendum: http://www.sciencedirect.com/science/article/pii/S0167865514003468
96 (19). A. Solé-Ribalta, D. Sánchez, M. Batet, F. Serratosa, Towards the estimation of feature-based semantic similarity using multiple ontologies, Knowledge-Based Systems 55, pp: 101 - 113, 2014. http://dx.doi.org/10.1016/j.knosys.2013.10.015
----2013----
95. X. Cortés, C. Moreno & F. Serratosa, Improving the Correspondence Establishment based on Interactive Homography Estimation, Computer Analysis of Images and Patterns, CAIP2013, York, Unated Kindom, LNCS 8048 , pp: 457-465, 2013. http://dx.doi.org/10.1007/978-3-642-40246-3_57
94. X. Cortés & F. Serratosa, Active-Learning Query Strategies applied to select a Graph Node given a Graph Labelling, Graph based Representations GbR2013, Austria, Vienna, LNCS 7877, pp: 61-70, 2013. http://dx.doi.org/10.1007/978-3-642-38221-5_7
93 (18). A. Solé & F. Serratosa, Graduated Assignment Algorithm for Multiple Graph Matching based on a Common Labelling, International Journal of Pattern Recognition and Artificial Intelligence 27 (1), pp: 1350001 [27 pages], 2013. http://dx.doi.org/10.1142/S0218001413500018
92 (17). F. Serratosa, X. Cortés & A. Solé, Component Retrieval based on a Database of Graphs for Hand-Written Electronic-Scheme Digitalisation, Expert Systems With Applications 40, pp: 2493 -2502, 2013. http://dx.doi.org/10.1016/j.eswa.2012.10.071
----2012----
91 (16). A. Solé, F. Serratosa & A. Sanfeliu, On the Graph Edit Distance cost: Properties and Applications, International Journal of Pattern Recognition and Artificial Intelligence 26 (5), 1260004 [21 pages], 2012. http://dx.doi.org/10.1142/S021800141260004X
90. X. Cortés, F. Serratosa & A. Solé, A comparison between Structural and Embedding methods for Graph Classification, Syntactic and Structural Pattern Recognition, SSPR2012, Hiroshima, Japan, LNCS 7626 , pp: 234-242, 2012. ISBN: 978-3-642-34165-6. http://dx.doi.org/10.1007/978-3-642-34166-3_26
89. N. Rebagliati, A. Solé, M. Pelillo & F. Serratosa, On The Relation Between The Common Labelling and The Median Graph, Syntactic and Structural Pattern Recognition, SSPR2012, Hiroshima, Japan, LNCS 7626 , pp: 107-115, 2012. ISBN: 978-3-642-34165-6. http://dx.doi.org/10.1007/978-3-642-34166-3_12
88. F. Serratosa, X. Cortés & A. Solé, Graph Database Retrieval based on Metric-Trees, Syntactic and Structural Pattern Recognition, SSPR2012, Hiroshima, Japan, LNCS 7626 , pp: 437-447, 2012. ISBN: 978-3-642-34165-6. http://dx.doi.org/10.1007/978-3-642-34166-3_48
87. X. Cortés, F. Serratosa & A. Solé, Active Graph Matching based on Pairwise Probabilities between nodes, Syntactic and Structural Pattern Recognition, SSPR2012, Hiroshima, Japan, LNCS 7626 , pp: 98-106, 2012. ISBN: 978-3-642-34165-6. http://dx.doi.org/10.1007/978-3-642-34166-3_11
86. F. Serratosa, X. Cortés, A. Solé, Interactive Graph Matching by means of Imposing the Pairwise Costs, International Conference on Pattern Recognition, ICPR2012, Tsukuba, Japan, pp: 1298 - 1301, 2012. ISBN: 978-4-9906441-1-6. http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6460377
85. N. Rebagliati, A. Solé, M. Pelillo, F. Serratosa, Computing the Graph Edit Distance Using Dominant Sets, International Conference on Pattern Recognition, ICPR2012, Tsukuba, Japan, pp: 1080-1083, 2012. ISBN: 978-4-9906441-1-6. http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?reload=true&arnumber=6460323
84 (15). G. Sanromà, R. Alquézar, F. Serratosa & B. Herrera, Smooth Point-set Registration using Neighbouring Constraints, Pattern Recognition Letters 33, pp: 2029-2037, 2012. http://dx.doi.org/10.1016/j.patrec.2012.04.008
83 (14). F. Serratosa, R. Alquézar & N. Amézquita, A Probabilistic Integrated Object Recognition and Tracking Framework, Expert Systems With Applications 39, pp: 7302-7318, 2012. http://dx.doi.org/10.1016/j.eswa.2012.01.088
82. A. Solé, G. Sanromà, F. Serratosa & R. Alquézar, Group-wise sparse correspondences between images based on a common labelling approach, International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISAPP2012, Rome, Italy, Volume 1, pp: 269-278, 2012.
81 (13). G. Sanromà, R. Alquézar, & F. Serratosa, A New Graph Matching Method for Point-Set Correspondence using the EM Algorithm and Softassign, Computer Vision and Image Understanding 116(2), pp: 292-304, 2012. http://dx.doi.org/10.1016/j.cviu.2011.10.009
80 (12). D. Sánchez, A. Solé, M. Batet & F. Serratosa, Enabling semantic similarity estimation across multiple ontologies: an evaluation in the biomedical domain, Journal of Biomedical Informatics 45 (1), pp: 141-155, 2012. http://dx.doi.org/10.1016/j.jbi.2011.10.005
----2011----
79. F. Serratosa, A. Solé & X. Cortés, K-nn queries in Graph Databases using M-Trees, Computer Analysis of Images and Patterns, CAIP2011, Seville, Spain, LNCS 6854, pp: 202-210, 2011. http://dx.doi.org/10.1007/978-3-642-23672-3_25
78 (11). A. Solé & F. Serratosa, Models and Algorithms for computing the Common Labelling of a set of Attributed Graphs, Computer Vision and Image Understanding 115 (7), pp: 929-945, 2011. http://dx.doi.org/10.1016/j.cviu.2010.12.007
77. F. Serratosa, A. Solé & X. Cortés, Automatic Learning of Edit Costs based on Interactive & Adaptive Graph Recognition, Graph based Representations, GbR2011, Munster, Germany, LNCS 6658 pp: 152,163, 2011. http://dx.doi.org/10.1007/978-3-642-20844-7_16
76. G. Sanromà, R. Alquézar, & F. Serratosa, Smooth Simultaneous Structural Graph Matching and Point-Set Registration, Graph based Representations, GbR2011, Munster, Germany, LNCS 6658 pp: 142,151 2011. http://dx.doi.org/10.1007/978-3-642-20844-7_15
75. A. Solé & F. Serratosa, Exploration of the labelling Space given graph edit distance costs, Graph based Representations, GbR2011, Munster, Germany, LNCS 6658 pp: 164,174, 2011. http://dx.doi.org/10.1007/978-3-642-20844-7_17
74. D. Ródenas, F. Serratosa & A. Solé, Parallel Graduated Assignment Algorithm for Multiple Graph Matching based on a Common Labelling, Graph based Representations, GbR2011, Munster, Germany, LNCS 6658 pp: 132,141, 2011. http://dx.doi.org/10.1007/978-3-642-20844-7_14
73. D. Ródenas, F. Serratosa & A. Solé, Graph Matching on a Low-cost & Parallel Architecture, Iberian Conference on Pattern Recognition and Image Analysis, IBPRIA2011, Gran Canaria, Spain, LNCS 6669, pp: 508-515, 2011. http://dx.doi.org/10.1007/978-3-642-21257-4_63
72. F. Serratosa & A. Solé, A Probabilistic Framework to obtain a Common Labelling between Attributed Graphs, Iberian Conference on Pattern Recognition and Image Analysis, IBPRIA2011, Gran Canaria, Spain, LNCS 6669, pp: 180-190, 2011. http://dx.doi.org/10.1007/978-3-642-21257-4_64
----2010----
71. F. Serratosa, A. Solé & E. Vidiella, Graph Indexing and Retrieval based on Median Graphs, Mexican Conference on Pattern Recognition, MCPR2010, Puebla, Mexico, LNCS 6256, pp: 311-321, 2010. http://dx.doi.org/10.1007/978-3-642-15992-3_33
70. A. Solé & F. Serratosa, Graduated Assignment Algorithm for Finding the Common Labelling of a set of Graphs, Syntactic and Structural Pattern Recognition, SSPR2010, Izmir, Turkey, LNCS 6218, pp: 180-190, 2010. http://dx.doi.org/10.1007/978-3-642-14980-1_17
69. G. Sanromà, R. Alquézar & F. Serratosa, Attributed Graph Matching for Image-Features Association using SIFT Descriptors, Syntactic and Structural Pattern Recognition, SSPR2010, Izmir, Turkey, LNCS 6218, pp: 254-263, 2010. http://dx.doi.org/10.1007/978-3-642-14980-1_24
68. G. Sanromà, R. Alquézar & F. Serratosa, A Discrete Labelling Approach to Attributed Graph Matching using SIFT Features, International Conference on Pattern Recognition, ICPR2010, Istanbul, Turkey, pp: 954-957, 2010. http://dx.doi.org/10.1109/ICPR.2010.239
67. G. Sanromà, R. Alquézar & F. Serratosa, Graph Matching using SIFT Descriptors, an application to pose recovery of a mobile robot, International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISAPP2010, Angers, France, pp: 249-254, 2010.
66 (10). M. Ferrer, E. Valveny, F. Serratosa, K. Riesen & H. Bunke. Generalized Median Graph Computation by Means of Graph Embedding in Vector Spaces, Pattern Recognition 43 (4), pp: 1642-1655, 2010. http://dx.doi.org/10.1016/j.patcog.2009.10.013
----2009----
65. F. Serratosa, N. Amézquita & R. Alquézar, Experimental Assessment of Probabilistic Integrated Object Recognition and Tracking Methods, Iberoamerican Congress on Pattern Recognition, CIARP2009, Guadalajara, México, LNCS 5859, pp: 817-824, 2009. http://dx.doi.org/10.1007/978-3-642-10268-4_96
64. A. Solé & F. Serratosa, On the Computation of the Common Labelling of a Set of Attributed Graphs, Iberoamerican Congress on Pattern Recognition, CIARP2009, Guadalajara, México, LNCS 5859, pp: 137-144, 2009. http://dx.doi.org/10.1007/978-3-642-10268-4_16
63. M. Ferrer, E. Valveny, F. Serratosa, I. Bardaj_ & H. Bunke, Graph-Based k-Means Clustering: A Comparison of the Set Median versus the Generalized Median Graph, Computer Analysis of Images and Patterns, CAIP2009: Munster, Germany, LNCS 5702, pp: 342-350, 2009. http://dx.doi.org/10.1007/978-3-642-03767-2_42
62 (9). M. Ferrer, E. Valveny & F. Serratosa, Median graphs: A genetic approach based on new theoretical properties, Pattern Recognition 42 (9), pp: 2003-2012, 2009. http://dx.doi.org/10.1016/j.patcog.2009.01.034
61 (8). M. Ferrer, E. Valveny & F. Serratosa: Median graph: A new exact algorithm using a distance based on the maximum common subgraph, Pattern Recognition Letters 30 (5), pp: 579-588, 2009. http://dx.doi.org/10.1016/j.patrec.2008.12.014
60. A. Solé & F. Serratosa, A structural and semantic probabilistic model for matching and representing a set of graphs, Graph Based Representations, GbR2009, Venice, Italy, LNCS 5534, pp: 164-173, 2009. http://dx.doi.org/10.1007/978-3-642-02124-4_17
59. M. Ferrer, E. Valveny & F. Serratosa, Median Graph Computation by means of a Genetic Approach Based on Minimum Common Supergraph and Maximum Common Subgraph, Pattern Recognition and Image Analysis, Fourth Iberian Conference, IbPRIA2009, LNCS 5524, Oporto, Portugal, pp: 346-353, 2009. http://dx.doi.org/10.1007/978-3-642-02172-5_45
58. R. Alquézar, N. Amézquita & F. Serratosa, Tracking Deformable Objects and Dealing with same class Object Occlusion, International Conference on Computer Vision Theory and Applications, VISAPP2009, Lisbon, Portugal, pp: 590-594 , 2009.
----2008----
57. G. Sanromà, F. Serratosa & R. Alquézar, Shape Learning with Function-Described Graphs, International Congress on Image Analysis and Recognition, ICIAR2008, LNCS 5112, Povoa de Varzim, Portugal, pp: 475-484, 2008. http://dx.doi.org/10.1007/978-3-540-69812-8_47
56. N. Amézquita, R. Alquézar & F. Serratosa, Dealing with Occlusion in a Probabilistic Object Tracking Method, IEEE Computer Vision and Pattern Recognition, CVPR2008, Anchorage, Alaska, USA, CVPRW, Print ISBN: 978-1-4244-2339-2, pp: 1-8, 2008.
55. G. Sanromà, F. Serratosa & R. Alquézar, Hybrid Genetic Algorithm and Procrustes Analysis for Enhancing the Matching of Graphs Generated from Shapes, Proc. Syntactic and Structural Pattern Recognition, SSPR2008, LNCS 5342, Orlando, Florida, USA, pp: 298-307, 2008. http://dx.doi.org/10.1007/978-3-540-89689-0_34
54. M. Ferrer, E. Valveny, F. Serratosa & H. Bunke, Exact Median Graph Computation via Graph Embedding, Syntactic and Structural Pattern Recognition, SSPR2008, LNCS 5342, Orlando, Florida, pp: 15-24, 2008. http://dx.doi.org/10.1007/978-3-540-89689-0_6
53. G. Sanromà, F. Serratosa & R. Alquézar, Improving the Matching of Graphs Generated from Shapes by the Use of Procrustes Distances into a Clique-based MAP Formulation, 19th International Conference on Pattern Recognition, ICPR2008, Tampa, Florida, USA, Volume 2, pp: 1-4, 2008. http://dx.doi.org/10.1109/ICPR.2008.4761107
52. M. Ferrer, E. Valveny, F. Serratosa, K. Riesen & H. Bunke An Approximate Algorithm for Median Graph Computation using Graph Embedding, 19th International Conference on Pattern Recognition, ICPR2008, Tampa, Florida, USA, Volume 2, pp: 1-4, 2008. http://dx.doi.org/10.1109/ICPR.2008.4761354
51 (7). F. Serratosa & G. Sanromà, A Fast Approximation of the Earth-Movers Distance between Multi-Dimensional Histograms, International Journal of Pattern Recognition and Artificial Intelligence 22 (8), pp: 1539 -1558, 2008. http://dx.doi.org/10.1142/S0218001408006880
----2007----
50. M. Ferrer, E. Valveny & F. Serratosa, Bounding the Size of the Median Graph, Pattern Recognition and Image Analysis, Third Iberian Conference, IbPRIA2007, LNCS 4478, Girona, Spain, pp: 491-498, 2007. http://dx.doi.org/10.1007/978-3-540-72849-8_62
49. M. Ferrer, F. Serratosa & E. Valveny, Evaluation of the Spectral Methods for Median Graph Computation, Pattern Recognition and Image Analysis, Third Iberian Conference, IbPRIA2007, LNCS 4478, Girona, Spain, pp: 580-587, 2007. http://dx.doi.org/10.1007/978-3-540-72849-8_73
48. M. Ferrer, F. Serratosa & E. Valveny, On the relation between the median and the maximum common subgraph of a set of graphs, 6th IAPR -TC-15 Workshop on Graph-based Representations in Pattern Recognition, Gbr2007, LNCS 4538, Alacant, Spain, pp: 351-360 , 2007. http://dx.doi.org/10.1007/978-3-540-72903-7_32
47. N. Amézquita, R. Alquézar & F. Serratosa, A New Method for Object Tracking Based on Regions Instead of Contours, IEEE Computer Vision and Pattern Recognition, CVPR2007, Minneapolis, Minnesota, USA, Print ISBN: 1-4244-1180-7, pp: 1 -8 , 2007.
46. F. Serratosa, G. Sanromà, & A. Sanfeliu, A New Algorithm to Compute the Distance between Multi-dimensional Histograms, Iberoamerican Congress on Pattern Recognition, CIARP2007, LNCS, 4756, Villa del Mar-Valparaiso, Chile, pp: 115 - 123, 2007. http://dx.doi.org/10.1007/978-3-540-76725-1_13
45. F. Serratosa & G. Sanromà, Modelling Intermittently Present Features using non-Linear Point Distribution Models, IEEE, Pacific-Rim on Image and Video Technology, PSIVT2007, LNCS 4872, Santigao, Chile, pp: 260-273 , 2007. http://dx.doi.org/10.1007/978-3-540-77129-6_25
----2006----
44 (6). F. Serratosa, A. Sanfeliu, Signatures versus histograms: Definitions, distances and algorithms. Pattern Recognition 39 (5), pp: 921-934, 2006. http://dx.doi.org/10.1016/j.patcog.2005.12.005
43. F. Serratosa & G. Sanromà, An Efficient Distance between Multi-dimensional Histograms for Comparing images, Proc. Syntactic and Structural Pattern Recognition, SSPR2006, LNCS 4109, Hong Kong China, pp: 412-421, 2006. http://dx.doi.org/10.1007/11815921_45
42. F. Serratosa & A. Sanfeliu, A Fast and Exact Modulo-Distance between Histograms, Proc. Syntactic and Structural Pattern Recognition, SSPR2006, LNCS 4109, Hong Kong, China, pp: 394-402, 2006. http://dx.doi.org/10.1007/11815921_43
41. F. Serratosa & A. Sanfeliu, Vision-Based Robot Positioning by an Exact Distance Between Histograms, 18th International Conference on Pattern Recognition, ICPR2006, Hong Kong China, Volume 2, pp: 849-852, 2006. http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.1179
40. M. Ferrer, E. Valveny & F. Serratosa, Spectral median graphs applied to graphical recognition, 11th Iberoamerican Congress on Pattern Recognition, CIARP2006, LNCS, 4225, Cancun, Mexico, pp: 774-783 , 2006. http://dx.doi.org/10.1007/11892755_80
39. N. Amézquita, R. Alquézar & F. Serratosa, Object recognition and tracking in video sequences: a new integrated methodology, 11th Iberoamerican Congress on Pattern Recognition, CIARP2006, LNCS, 4225, Cancun, Mexico, pp: 481-490 , 2006. http://dx.doi.org/10.1007/11892755_50
38. F. Serratosa, N. Amézquita & R. Alquézar, Combining neural networks and clustering techniques for object recognition in indoor video sequences, 11th Iberoamerican Congress on Pattern Recognition, CIARP2006, LNCS, 4225, Cancun, Mexico, pp: 399-405, 2006. http://dx.doi.org/10.1007/11892755_41
----2005----
37 (5). E. Staffeti, A. Grau, F. Serratosa & A. Sanfeliu, Object and Image indexing based on Region Connection Calculus and Oriented Matroids theory, Discrete Applied Mathematics 147 (2-3), pp: 345-361, 2005. http://dx.doi.org/10.1016/j.dam.2004.09.019
36. F. Serratosa & A. Sanfeliu, Matching Attributed Graphs: Second Order Probabilities for pruning the search tree, Pattern Recognition and Image Analysis, Second Iberian Conference, IbPRIA2005, LNCS 3523, Estoril, Portugal, pp: 131-138, 2005. http://dx.doi.org/10.1007/11492542_17
35. M. Ferrer, F. Serratosa & A. Sanfeliu, Synthesis of Median Spectral Graphs, Pattern Recognition and Image Analysis, Second Iberian Conference, IbPRIA2005, LNCS 3523, Estoril, Portugal, pp: 139-146, 2005. http://dx.doi.org/10.1007/11492542_18
34. F. Serratosa & A. Sanfeliu, A Fast Distance Between Histograms, Progress in Pattern Recognition, Image Analysis and Applications: 10th Iberoamerican Congress on Pattern Recognition, CIARP2005, LNCS 3773, Havana, Cuba, pp. 1027-1035, 2005. http://dx.doi.org/10.1007/11578079_105
----2004----
33 (4). A. Sanfeliu, F. Serratosa & R. Alquézar, Second-Order Random Graphs for modelling sets of Attributed Graphs and their application to object learning and recognition, International Journal of Pattern Recognition and Artificial Intelligence 18 (3), pp: 375-396, 2004. http://dx.doi.org/10.1142/S0218001404003253
32. F. Serratosa & A. Sanfeliu, Distance measures between Attributed Graphs and Second-order Random Graphs, Proc. Syntactic and Structural Pattern Recognition, SSPR2004, LNCS 3138, pp: 1135-1144, 2004. http://dx.doi.org/10.1007/978-3-540-27868-9_125
31. F. Serratosa, A. Grau, & A. Sanfeliu, Distance between 2D-scenes based on Oriented Matroids theory, 17th International Conference on Pattern Recognition, ICPR2004, Cambridge, United Kingdom, Volume 2, pp: 196-199, 2004. http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334094
----2003----
30 (3). F. Serratosa, R. Alquézar & A. Sanfeliu, Function-Described Graphs for modelling objects represented by attributed graphs, Pattern Recognition 36 (3), pp: 781-798, 2003. http://dx.doi.org/10.1016/S0031-3203(02)00107-3
29. E. Staffeti, A. Grau, F. Serratosa & A. Sanfeliu, Oriented Matroids for Shape Representation and Indexing, Pattern Recognition and Image Analysis, First Iberian Conference, IbPRIA2003, LNCS 2652, Palma de Mallorca, Spain, pp: 1012-1019, 2003. http://dx.doi.org/10.1007/978-3-540-44871-6_117
28. E. Staffeti, A. Grau, F. Serratosa & A. Sanfeliu, Indexación de Imágenes Basada en la Teoría de las Matroides Orientadas, Jornadas de Automática, León Spain, 2003.
27. A. Sanfeliu & F. Serratosa, Learning and recognising 3D models represented by multiple views by means of methods based on random graphs, International Congress on Image Processing, ICIP2003, Barcelona, Spain, Volume 2 pp: 29,32, 2003.
26. E. Staffeti, A. Grau, F. Serratosa & A. Sanfeliu, Shape Representation and Indexing based on Region Connection Calculus and Oriented Matroids theory, Discrete Geometry for Computer Imagery, 11th International Conference, DGCI2003, LNCS 2886, Napoli, Italy, pp: 267-276, 2003. http://dx.doi.org/10.1007/978-3-540-39966-7_25
----2002----
25 (2). A. Sanfeliu, R. Alquézar, J. Andrade, J. Climent, F. Serratosa & J. Vergés, Graph-based Representations and Techniques for Image Processing and Image Analysis, Pattern Recognition 35 (3), pp: 639-650, 2002. http://dx.doi.org/10.1016/S0031-3203(01)00066-8
24. F. Serratosa, R. Alquézar & A. Sanfeliu, Estimating the Joint Probability Distribution of Random Vertices and Arcs by means of Second-order Random Graphs, Proc. Syntactic and Structural Pattern Recognition, SSPR2002, LNCS 2396, Windsor, Canada, pp: 252-262, 2002. http://dx.doi.org/10.1007/3-540-70659-3_26
23. A. Grau, J. Climent, F. Serratosa & A. Sanfeliu, Textprint: A new algorithm to discriminate textures structurally, Syntactic and Structural Pattern Recognition, SSPR2002, LNCS 2396, Windsor, Canada, pp: 368-377, 2002. http://dx.doi.org/10.1007/3-540-70659-3_38
22. F. Serratosa, R. Alquézar & A. Sanfeliu, Modelling and recognising 3D-objects described by multiple views using Function-Described Graphs, 16th International Conference on Pattern Recognition, ICPR2002, Quebec, Canada, vol. 2, pp: 140-143, 2002. http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1048257
21(1). F. Serratosa, R. Alquézar & A. Sanfeliu, Synthesis of function-described graphs and clustering of attributed graphs, International Journal of Pattern Recognition and Artificial Intelligence 16 (6), pp: 621-655, 2002. http://dx.doi.org/10.1142/S0218001402001915
----2001----
20. A. Sanfeliu, J. Andrade-Cetto, R. Alquézar, J. Aranda, J. Climent, A. Grau, F. Serratosa & J. Vergés-Llahí, MARCO: A mobile robot with learning capabilities to perceive and interact with its environment, Simposium Nacional de Reconocimiento de Formas y Analisis de Im_genes, SNRFAI2001, Castelló, Spain, vol. 2, pp: 219-224, 2001.
----2000----
19. F. Serratosa, A. Sanfeliu & R. Alquézar, Function-Described Graphs: A measure of similarity based on probabilities, Pattern Recognition and Applications, IOS Press, Edited by M.I. Torres and A. Sanfeliu, pp: 59-68, 2000.
18. F. Serratosa, R. Alquézar & A. Sanfeliu, Efficient algorithms for matching attributed graphs and function-described graphs, Proc.15th International Conference on Pattern Recognition, ICPR2000, Barcelona, Spain, vol. 2, pp: 871-876, 2000. http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.906212
17. Sanfeliu, F. Serratosa & R. Alquézar, Clustering of attributed graphs and unsupervised synthesis of function-described graphs, Proc. 15th International Conference on Pattern Recognition, ICPR2000, Barcelona, Spain, vol. 2, pp: 1026-1029, 2000. http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.906248
16. R. Alquézar, F. Serratosa & A. Sanfeliu, Distance measures between Attributed Graphs and Function-Described Graphs relaxing 2nd-order constraints, Proc. Syntactic and Structural Pattern Recognition, SSPR2000, LNCS 1876, Alacant, Spain, pp: 277-286, 2000. http://dx.doi.org/10.1007/3-540-44522-6_29
15. A. Sanfeliu, A. Grau, J. Climent, R. Alquézar, F. Serratosa, J. Aranda, J. Vergés-Llahí & J. Andrade-Cetto, Pattern Recognition at the IRI-CSIC/ESAII Group, Pattern Recognition Advances in Iberoamerica, FORO2000, Barcelona, Spain, pp. 347-354, 2000.
14. F. Serratosa, Function-Described Graphs for Structural Pattern Recognition. Doctoral PhD, Universitat Politècnica de Catalunya, 2000. http://deim.urv.cat/~francesc.serratosa/FDG_Thesis_Dissertation.pdf
----1999----
13. F. Serratosa, A. Sanfeliu & R. Alquézar, Function-described graphs: an improvement on random graphs. IV Simposium Iberoamericano de Reconocimiento de Patrones, SIARP1999, La Habana, Cuba, pp. 655-665, 1999.
12. F. Serratosa, A. Sanfeliu & R. Alquézar, Function-Described Graphs: A measure of similarity based on probabilities, 8th National Symposium on Pattern Recognition and Image Analysis, NSPRIA1999, Bilbao, Spain, Vol. I, pp. 421-428, 1999.
11. J. Vergés-Lahí, A. Sanfeliu, F. Serratosa & R. Alquézar, Face recognition: Graph matching versus neural techniques, 8th National Symposium on Pattern Recognition and Image Analysis, NSPRIA1999, Bilbao, Spain, Vol. I, pp. 259-266, 1999.
10. D. Riaño & F. Serratosa, Unsupervised synthesis of Function-Described Graphs, Proceedings of the 2ond Workshop on Graph Based Representations GbR1999, pp: 165-171, Vienna, Austria, 1999.
9. F. Serratosa, R. Alquézar & A. Sanfeliu, Function-Described Graphs: A fast algorithm to compute a sub-optimal matching measure, Proceedings of the 2ond Workshop on Graph Based Representations GbR1999, pp: 71-77, Vienna, Austria, 1999.
8. F. Serratosa, R. Alquézar & A. Sanfeliu, Function-Described Graphs for structural pattern recognition, Technical report DEIM-RR-99-006, Universitat Rovira i Virgili, Tarragona, Spain, 1999.
----1998----
7. R. Alquézar, A. Sanfeliu & F. Serratosa, Synthesis of Function-Described Graphs, Advances in Pattern Recognition, Proc. Joint IAPR Int. Workshops SSPR1998 and SPR1998, SSPR1998, LNCS 1451,Sydney, Australia, pp. 112-121, 1998. http://dx.doi.org/10.1007/BFb0033229
6. F. Serratosa, A. Sanfeliu & R. Alquézar, Function-described graphs: Distance and matching. Technical Report IRI-DT-9803, Universitat Politècnica de Catalunya, Institut de Robòtica i Informàtica Industrial, Barcelona, Spain, 1998.
----1997----
5. F. Serratosa & A. Sanfeliu, Function-Described Graphs applied to 3D object recognition. 9th Int. Conf. Image Analysis and Processing, Image Analysis and Processing, ICIAP1997, LNCS 1310, Firenze, Italy, Vol. I, pp. 701-708, 1997. http://dx.doi.org/10.1007/3-540-63507-6_263
4. F. Serratosa & A. Sanfeliu, Function-Described Graphs. 7th National Symposium on Pattern Recognition and Image Analysis, NSPRIA1997, Barcelona, Spain, Vol. I, pp. 37-42, 1997.
----1995----
3. F. Serratosa, Comparación de cadenas para el reconocimiento de patrones, Seminario anual de automática y electrónica industrial SAAEI1995, Tarragona, Spain, pp. 469-472, 1995.
2. 1995. F. Serratosa, P. Millán & E. Montseny, Systolic processors applied to computer vision systems. Computer Architectures for Machine Perception CAMP1995, Como, Italy, pp. 178-183, 1995.
----1994----
1. P. Millán, F. Serratosa & E. Montseny, Procesadores sistólicos aplicados a visión por computador. III Jornadas de Visión por Computador JVC1994, Málaga, Spain, pp. 167-178, 1994.