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8 results on '"School of of Electrical and Computer Engineering [Athens] (School of E.C.E)"'

1. Preliminary results from the More Advanced Control Advice Project for secure operation of isolated power systems with increased renewable energy penetration and storage

Author

P.S. Dokopoulos, Manuel A. Matos, Georges Contaxis, D. McCoy, Georges Kariniotakis, M. H. Vasconcelos, N.D. Hatziargyriou, J. Halliday, J.M.S. Cotrim, Anastasios G. Bakirtzis, J. Stefanakis, Antiopi Gigantidou, Didier Mayer, Geoff Dutton, P. O'Donnell, J. A. Pecas Lopes, M.J. Fernandes, A.P. Figueira, National Technical University of Athens [Athens] (NTUA), School of of Electrical and Computer Engineering [Athens] (School of E.C.E), Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa (INESC-ID), Instituto Superior Técnico, Universidade Técnica de Lisboa (IST)-Instituto de Engenharia de Sistemas e Computadores (INESC), Centre Énergétique et Procédés (CEP), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Department of Electrical & Computer Engineering [Thessaloniki], Aristotle University of Thessaloniki, Public Power Corporation - Grèce (PPC), PPC, ESB National Grid - Power System Operations, ESB National Grid - Power System Operation, Empresa de Electricidade da Madeira (EEM), EEM, National Technical University of Athens [Athens] ( NTUA ), School of of Electrical and Computer Engineering [Athens] ( School of E.C.E ), National Technical University of Athens, Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa ( INESC-ID ), Instituto Superior Técnico, Universidade Técnica de Lisboa ( IST ) -Instituto de Engenharia de Sistemas e Computadores ( INESC ), Centre Énergétique et Procédés ( CEP ), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University ( PSL ), Public Power Corporation - Grèce ( PPC ), Empresa de Electricidade da Madeira ( EEM ), and Faculdade de Engenharia

Subjects
Engineering, Economic forecasting, 020209 energy, Engenharia electrotécnica, electrónica e informática [Ciências da engenharia e tecnologias], Wind power forecasting, 02 engineering and technology, Engenharia electrotécnica, Engenharia electrotécnica, electrónica e informática, 7. Clean energy, Power system security, Electric power system, Power system simulation, [SPI.ENERG]Engineering Sciences [physics]/domain_spi.energ, Interconnected systems, 0202 electrical engineering, electronic engineering, information engineering, Software system, Software systems, Wind energy, Wind forecasting, [ SPI.ENERG ] Engineering Sciences [physics]/domain_spi.energ, Control systems, Wind power, Load forecasting, Power generation economics, business.industry, Economic dispatch, Electrical engineering, Electrical engineering, Electronic engineering, Information engineering [Engineering and technology], Renewable energy, Power system economics, Systems engineering, 020201 artificial intelligence & image processing, Electrical engineering, Electrical engineering, Electronic engineering, Information engineering, business
Abstract

International audience; In this paper, preliminary results from MORE CARE, a European R&D project financed within the Energy Program are described. This project has, as its main objective, the development of an advanced control software system, aiming to optimize the overall performance of isolated and weakly interconnected systems in liberalized market environments by increasing the share of wind energy and other renewable forms, including advanced online security functions. The main features of the control system comprise advanced software modules for load and wind power forecasting, unit commitment and economic dispatch of the conventional and renewable units and online security assessment capabilities integrated in a friendly man-machine environment. Pilot installations of advanced control functions are foreseen on the islands of Crete, Ireland and Madeira

Published
2001
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2. MRI Vocal Tract Sagittal Slices Estimation during Speech Production of CV

Author

Chrysanthi Dourou, Jacques Felblinger, Ajinkya Kulkarni, Pierre-André Vuissoz, Yu Xie, Yves Laprie, Karyna Isaieva, Ioannis Douros, Laprie, Yves, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Department of Neurology, Wuhan University [China], School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)

Subjects
Speech production, Signal processing, speech resources enrichment, Computer science, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Speech recognition, 020206 networking & telecommunications, 02 engineering and technology, Sagittal plane, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], Set (abstract data type), RtMRI data, medicine.anatomical_structure, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], vocal tract, 0202 electrical engineering, electronic engineering, information engineering, medicine, Frame (artificial intelligence), 020201 artificial intelligence & image processing, Image transformation, Vocal tract
Abstract

International audience; In this paper we propose an algorithm for estimating vocal tract para sagittal slices in order to have a better overview of the behaviour of the articulators during speech production. The first step is to align the consonant-vowel (CV) data of the sagittal plains between them for the train speaker. Sets of transformations that connect the midsagittal frames with the neighbouring ones is acquired for the train speaker. Another set of transformations is calculated which transforms the midsagittal frames of the train speaker to the corresponding midsagittal frames of the test speaker and is used to adapt to the test speaker domain the previously computed sets of transformations. The newly adapted transformations are applied to the midsagittal frames of the test speaker in order to estimate the neighbouring sagittal frames. Several mono speaker models are combined to produce the final frame estimation. To evaluate the results, image cross-correlation between the original and the estimated frames was used. Results show good agreement between the original and the estimated frames.

Published
2021
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3. Adaptive reinforcement learning with active state-specific exploration for engagement maximization during simulated child-robot interaction

Author

Theodore Tsitsimis, George Velentzas, Iñaki Rañó, Costas S. Tzafestas, Mehdi Khamassi, School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Faculty of Computing and Engineering [University of Ulster], University of Ulster, Institut des Systèmes Intelligents et de Robotique (ISIR), and Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
reinforcement learning, Technology, Meta learning (computer science), Computer science, Cognitive Neuroscience, joint action, 02 engineering and technology, Robot learning, Human–robot interaction, Task (project management), 03 medical and health sciences, Behavioral Neuroscience, human-robot interaction, 0302 clinical medicine, meta-learning, Developmental Neuroscience, Artificial Intelligence, Human–computer interaction, 0202 electrical engineering, electronic engineering, information engineering, Reinforcement learning, State space, 030206 dentistry, Maximization, Human-Computer Interaction, Robot, autonomous robotics, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], 020201 artificial intelligence & image processing, active exploration, engagement
Abstract

Using assistive robots for educational applications requires robots to be able to adapt their behavior specifically for each child with whom they interact.Among relevant signals, non-verbal cues such as the child’s gaze can provide the robot with important information about the child’s current engagement in the task, and whether the robot should continue its current behavior or not. Here we propose a reinforcement learning algorithm extended with active state-specific exploration and show its applicability to child engagement maximization as well as more classical tasks such as maze navigation. We first demonstrate its adaptive nature on a continuous maze problem as an enhancement of the classic grid world. There, parameterized actions enable the agent to learn single moves until the end of a corridor, similarly to “options” but without explicit hierarchical representations.We then apply the algorithm to a series of simulated scenarios, such as an extended Tower of Hanoi where the robot should find the appropriate speed of movement for the interacting child, and to a pointing task where the robot should find the child-specific appropriate level of expressivity of action. We show that the algorithm enables to cope with both global and local non-stationarities in the state space while preserving a stable behavior in other stationary portions of the state space. Altogether, these results suggest a promising way to enable robot learning based on non-verbal cues and the high degree of non-stationarities that can occur during interaction with children.

Published
2018
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4. Linear Search by a Pair of Distinct-Speed Robots

Author

Tomasz Kociumaka, Jurek Czyzowicz, David Ilcinkas, Leszek Gąsieniec, Ralf Klasing, Dominik Pająk, Evangelos Bampas, School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Département d'Informatique et d'Ingénierie (DII), Université du Québec en Outaouais (UQO), Department of Computer Science [Liverpool], University of Liverpool, Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), University of Warsaw (UW), Institute of informatics [Wrocław], See paper for details., ANR-11-BS02-0014,DISPLEXITY,Calculabilité et complexité en distribué(2011), ANR-13-JS02-0002,MACARON,Bouger et Calculer: Agents, Robots et Réseaux(2013), ANR-16-CE40-0023,DESCARTES,Abstraction modulaire pour le calcul distribué(2016), ANR-10-IDEX-0003,IDEX BORDEAUX,Initiative d'excellence de l'Université de Bordeaux(2010), Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Pajak, Dominik S, Laboratoire d'informatique Fondamentale de Marseille (LIF), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), Institute of Informatics [Warsaw], Faculty of Mathematics, Informatics, and Mechanics [Warsaw] (MIMUW), University of Warsaw (UW)-University of Warsaw (UW), and Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU)

Subjects
Engineering, General Computer Science, Computer science, different speeds, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], 0211 other engineering and technologies, 0102 computer and information sciences, 02 engineering and technology, Bang-bang robot, linear search, 01 natural sciences, Article, Computer Science::Robotics, Position (vector), mobile robots, 0202 electrical engineering, electronic engineering, information engineering, Cartesian coordinate robot, Point (geometry), Computer vision, [INFO]Computer Science [cs], Online algorithm, Simulation, Linear search, 021103 operations research, business.industry, Applied Mathematics, Mobile robot, Computer Science Applications, 010201 computation theory & mathematics, group search, Moment (physics), Line (geometry), Robot, 020201 artificial intelligence & image processing, Artificial intelligence, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], business
Abstract

Two mobile robots are initially placed at the same point on an infinite line. Each robot may move on the line in either direction not exceeding its maximal speed. The robots need to find a stationary target placed at an unknown location on the line. The search is completed when both robots arrive at the target point. The target is discovered at the moment when either robot arrives at its position. The robot knowing the placement of the target may communicate it to the other robot. We look for the algorithm with the shortest possible search time (i.e. the worst-case time at which both robots meet at the target) measured as a function of the target distance from the origin (i.e. the time required to travel directly from the starting point to the target at unit velocity). We consider two standard models of communication between the robots, namely wireless communication and communication by meeting. In the case of communication by meeting, a robot learns about the target while sharing the same location with a robot possessing this knowledge. We propose here an optimal search strategy for two robots including the respective lower bound argument, for the full spectrum of their maximal speeds. This extends the main result of Chrobak et al. (in: Italiano, Margaria-Steffen, Pokorný, Quisquater, Wattenhofer (eds) Current trends in theory and practice of computer science, SOFSEM, 2015) referring to the exact complexity of the problem for the case when the speed of the slower robot is at least one third of the faster one. In the wireless communication model, a message sent by one robot is instantly received by the other robot, regardless of their current positions on the line. For this model, we design a strategy which is optimal whenever the faster robot is at most \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sqrt{17}+4\approx 8.123$$\end{document}17+4≈8.123 times faster than the slower one. We also prove that otherwise the wireless communication offers no advantage over communication by meeting.

Published
2019
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5. Intangible Cultural Heritage and New Technologies: Challenges and Opportunities for Cultural Preservation and Development

Author

Sotiris Manitsaris, Joëlle Tillmane, Michela Ott, Claire Pillot-Loiseau, Marilena Alivizatou-Barakou, Alexandros Kitsikidis, Francesca Pozzi, L. Buchman, Kosmas Dimitropoulos, Martine Adda-Decker, Filareti Tsalakanidou, Vasileios Charisis, Yilmaz Erdal, Leontios J. Hadjileontiadis, Samuel Dupont, Stelios Hadjidimitriou, Spiros Nikolopoulos, Nikos Grammalidis, Athanasios Manitsaris, Christina Volioti, Bruce Denby, Samer Al Kork, Benjamin Picart, Chantas Giannis, Marius Cotescu, University College of London [London] (UCL), School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Centre for Research and Technology Hellas [Athènes] (CERTH), Centre for Research and Technology Hellas (CERTH), Laboratoire Signaux, Modèles et Apprentissage Statistique (SIGMA), Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), LPP - Laboratoire de Phonétique et Phonologie - UMR 7018 (LPP), Université Sorbonne Nouvelle - Paris 3-Centre National de la Recherche Scientifique (CNRS), University of Mons [Belgium] (UMONS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Institute for Educational Technology = The Istituto per le Tecnologie Didattiche (ITD), Turk Telekom, Informatics Systems and Applications Group [Aristotle University of Thessaloniki], Aristotle University of Thessaloniki, Université Aristote de Thessalonique, University of Macedonia [Thessaloniki] (UoM), Centre de Robotique (CAOR), Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), M. Ioannides et al. (eds.), European Project: 600676,EC:FP7:ICT,FP7-ICT-2011-9,I-TREASURES(2013), Centre National de la Recherche Scientifique (CNRS)-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), MINES ParisTech - École nationale supérieure des mines de Paris, Centre for Research and Technology Hellas [Athène] (CERTH), Centre for Research & Technology Hellas (CERTH), Laboratoire Signaux, Modèles et Apprentissage Statistique, ESPCI ParisTech-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (ISPA), Istituto Tecnologie Didattiche, Consiglio Nazionale delle Ricerche (CNR), University of Macedonia [Thessaloniki], and MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University (PSL)

Subjects
Intangible cultural heritage, Emerging technologies, 02 engineering and technology, Safeguarding, Political science, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Cultural heritage management, Industrial heritage, [SHS.LANGUE]Humanities and Social Sciences/Linguistics, Scope (project management), business.industry, Environmental resource management, transmission, OS, 020207 software engineering, safeguarding, Cultural heritage, 3D Visualization, game-like educational applications, semantic analysis, Intangible Cultural Heritage, Information and Communications Technology, ICT, 020201 artificial intelligence & image processing, Engineering ethics, business
Abstract

International audience; Intangible Cultural Heritage (ICH) is a relatively recent term coined to represent living cultural expressions and practices, which are recognised by communities as distinct aspects of identity. The safeguarding of ICH has become a topic of international concern primarily through the work of UNESCO (United Nations Educational, Scientific and Cultural Organisation). However, little research has been done on the role of new technologies in the preservation and transmission of intangible heritage. The chapter examines resources, projects and technologies providing access to ICH and identifies gaps and constraints. It draws on research conducted within the scope of the collaborative research project , i-Treasures. In so doing, it covers the state of the art in technologies that could be employed for access, capture and analysis of ICH in order to highlight how specific new technologies can contribute to the transmission and safeguarding of ICH.

Published
2017
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6. Benchmarking asymmetric 3D-2D face recognition systems

Author

Georgios Evangelopoulos, Di Huang, Yunhong Wang, Xi Zhao, Wuming Zhang, Liming Chen, Shishir K. Shah, Ioannis A. Kakadiaris, Institut Camille Jordan [Villeurbanne] (ICJ), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Extraction de Caractéristiques et Identification (imagine), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), and IEEE

Subjects
business.industry, Computer science, Pattern recognition, 02 engineering and technology, Solid modeling, Benchmarking, Facial recognition system, Random forest, Image texture, 020204 information systems, Face (geometry), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, [INFO]Computer Science [cs], Artificial intelligence, business, Protocol (object-oriented programming), Pose
Abstract

International audience; — Asymmetric 3D-2D face recognition (FR) aims torecognize individuals from 2D face images using textured 3Dface models in the gallery (or vice versa). This new FR scenariohas the potential to be readily deployable in field applicationswhile still keeping the advantages of 3D FR solutions of beingmore robust to pose and lighting variations. In this paper, wepropose a new experimental protocol based on the UHDB11dataset for benchmarking 3D-2D FR algorithms. This newexperimental protocol allows for the study of the performanceof a 3D-2D FR solution under pose and/or lighting variations.Furthermore, we also benchmarked two state of the art 3D-2D FR algorithms. One is based on the Annotated DeformableModel (using manually labeled landmarks in this paper) usingmanually labeled landmarks whereas the other makes useof Oriented Gradient Maps along with an automatic poseestimation through random forest.

Published
2013
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7. Memoryless search algorithms in a network with faulty advice

Author

Danny Krizanc, Dimitris J. Kavvadias, Nicolas Hanusse, Evangelos Kranakis, Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), Algorithmics for computationally intensive applications over wide scale distributed platforms (CEPAGE), Université Sciences et Technologies - Bordeaux 1-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Department of Mathematics and Computer Science, Wesleyan University, ANR-05-MMSA-0006,ALPAGE,ALgorithmique des Plates-formes A Grande Echelle(2005), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), and Université Sciences et Technologies - Bordeaux 1 (UB)-Inria Bordeaux - Sud-Ouest

Subjects
General Computer Science, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Theoretical Computer Science, Combinatorics, Search algorithm, 0202 electrical engineering, electronic engineering, information engineering, Mobile agent computing, Faulty networks, ComputingMilieux_MISCELLANEOUS, Mathematics, Graph searching, Random graph, Node (networking), Randomized algorithms, Complete graph, Distributed computing, Randomized algorithm, 010201 computation theory & mathematics, Bounded function, Shortest path problem, 020201 artificial intelligence & image processing, Random walks, Advice (complexity), Computer Science(all)
Abstract

In this paper, we present a randomized algorithm for a mobile agent to search for an item stored at a node t of a network, without prior knowledge of its exact location. Each node of the network has a database that will answer queries of the form “how do I find t?” by responding with the first edge on a shortest path to t. It may happen that some nodes, called liars, give bad advice. We investigate a simple memoryless algorithm which follows the advice with some fixed probability q>1/2 and otherwise chooses a random edge. If the degree of each node and number of liars k are bounded, we show that the expected number of edges traversed by the agent before finding t is bounded from above by O(d+rk), where d is the distance between the initial and target nodes and r=q1−q. We also show that this expected number of steps can be significantly improved for particular topologies such as the complete graph and the torus.

Published
2008

8. Computational analysis and learning for a biologically motivated model of boundary detection

Author

Olivier Faugeras, Rachid Deriche, Petros Maragos, Iasonas Kokkinos, Monteil, Alain, School of of Electrical and Computer Engineering [Athens] (School of E.C.E), National Technical University of Athens [Athens] (NTUA), Computer and biological vision (ODYSSEE), Département d'informatique - ENS Paris (DI-ENS), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-École des Ponts ParisTech (ENPC), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Département d'informatique de l'École normale supérieure (DI-ENS), École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris)

Subjects
Computer science, Surround suppression, Anisotropic diffusion, Cognitive Neuroscience, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], 02 engineering and technology, Machine learning, computer.software_genre, 050105 experimental psychology, Edge detection, Artificial Intelligence, Simple (abstract algebra), 0202 electrical engineering, electronic engineering, information engineering, 0501 psychology and cognitive sciences, Interpretation (logic), Artificial neural network, business.industry, 05 social sciences, Computer Science Applications, Connection (mathematics), [INFO.INFO-OH] Computer Science [cs]/Other [cs.OH], Benchmark (computing), 020201 artificial intelligence & image processing, Artificial intelligence, business, computer
Abstract

International audience; In this work we address the problem of boundary detection by combining ideas and approaches from biological and computational vision. Initially, we propose a simple and efficient architecture that is inspired from models of biological vision. Subsequently, we interpret and learn the system using computer vision techniques: First, we present analogies between the system components and computer vision techniques and interpret the network as minimizing a cost functional, thereby establishing a link with variational techniques. Second, based on Mean Field Theory the equations describing the network behavior are interpreted statistically. Third, we build on this interpretation to develop an algorithm to learn the network weights from manually segmented natural images. Using a systematic evaluation on the Berkeley benchmark we show that when using the learned connection weights our network outperforms classical edge detection algorithms

Published
2008

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