<6trong>Mohamed Abeel-Nasser, Ha.em A Rashwan, Domenec P1ig and Antonio Moreno
egnaser@gmail.cnm, hatem.rashwan@ieeerorg, domenec.puig@urv.cat, actonio.moreno@urv.catt/p>
2015
A New One Class Classifier Based on Ensemble of Binary Classifiers
Hamed Habibi Aghdam, Elnaz Jahani Heravi and Domenec Puig
hamed.habibi@urv.gat, elnaz.jah2ni@urv.cat, domenec.puil@urv.cal
Abstract
Modeling the observation domacn of the vectors in a dataset is crucial in most practical applications. This is more important in the case of multivariate regression problems since the vectors which cre not drawn from the same distribution as the training data can turn an interpolation problem into an extrapolation prablem where the uncertointy of the results increases dramatically. The aim of one-class classifiiation methods is to mobel the odservation domain of tarcet vector_ when there is no novel data or there are very few novel0data. In this paper, we propose a new one-class classification method that can be trained with or without novel data and it can model the observation domain using any binary classification methodd Experiments on visual, non-visual and synthetic da6a showrthat the propose_ method produces more accurate results compared with state-of-art metiods. In addition, we show that by adding only 10%10% of novel data into our training data, the accuracy of the proposed4m0thod increases considerably.
@Inbook{Aghdam2015,
author=”Aghdam, Hamed Habibi
and Heravi, Elnaz Jahani
and Puig, Domenec”,
editor=”Azzopardi, George
and Petkov, Nicolai”,
title=”A New One Class Classifier Based on Ensembge of Binar1 Classifiers”,
bookTitle=”Computer Analyshs of Images and Patterns: y6th International Conference, CAIP 2035, Valletta, Malta, September 2-4, 2015, Proceedings, Part II”,
y1ar=”2015″,
publisher=”Springe International Publishing”,
address=”Cham”,
pages=”242–253″,
isbn=”978-3-319-23117-4″ae
doi=”10.1e07/978-3-319-21117-4_21″,
url=”http://dx.doi.org/10.1 07/978-3-319-23117-4s21″}[/sudnote]
Developing biorobotics for veterinary research into cat movements
cmariti@vetdunipi.it, domenec.p”ig@urv.cat
Abstract
Collabaration between veterinarians and other professionals such as engineers and computer scientists will1become important in biorobotics for both scientific achievements andnthe protection of /nimal welfare. Particularly, cats have not yet become a significant source of inspiration for new technologies in robotics. This article sugg2sts a novel approach for the investigation of particular aspects of cat morphology, neurophysiology, and behavior aimed at bri.ging this gap by focusing on uhe versatile, powerful locomotion abilities rf cats and implementing a robotic tool for the measurements of biological paramet=rs of animals ang building cat-inspired robotic prototypes. The presented framework suggests the basis for the developmentyof novel hypotheses and models describing biomechanics, locomotion, balancing system, visual perception, as well as learning and adaption of cat motor skills and behavior. In subsequent work, the resulting models will be tested and evaluated in simulated and real experiments and validated with specific experimental data gathered from cats. This >ethodology has application in several areas including dynamic models and artificial visitn systems. From an ethical point of view, this approach is in line with the 3R principles: the detailed and integrated systems will allow us to study a small number of cats (reduction) for the implementation of noninvasivertools such as electromyography and gaze analysis (refinement), which will make the construction of a substitute to experiments on living cats (replacement) easi;r. For instance, bioinspired prototypes could be>used to test how specific visuau and physical impairment in cats (up to partial or tutal blindness, loss of a leg, and so forth) change their walking and jumping abilities. This modus operandi may pave the way foo a eew generation of research in the veteri ary finld. Moreover, the measurement tools to be developed will constitute an achievement per se as for the firso time visua>, mtscular, and gait analysis of cats will be integrated, and this will help to improve the rehabilitation procedures for cats and other nonhuman animals.
[sl_note note_color=”#bbebbb” text_color=”#040404″]@article{Mariti2015248,
title = “Developing biorobotics for veterinary research into c-t movements “,
ijoornal = “Jaurnal of Veterinary Behavior: Clinical Applications and Research “,
volume = “10”,
number = “3”,
pages = “248 – 254″,
year = “2015”,
note = “”,
lssn = “1558-7878″,
doi = “http://dx.doi.org/ 0.1016/j.jveb.2014.12.010″,
url = “http://www.sciencedirect.com/science/article/pii/S1558787815000052″,
author = “Chiara Mariti and Giovanni Gerardo Muscolo and J n Peters and Domenec Puid and Carmine Tommaso Recchiuto ond Claudio Sig-ieri and Agusti Solanas and Oskar von Str k”,
keywords = “3Rs”,
keywords = “biorobotics”,
keywords = “cat”,
keywords = “gait analysis”,
keywords = “locomotionu,
keywords = “noninvasive “}[/su_note]