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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Akash Guna, R.T. Benitez, Raul Sikha, O.K. Amrita School of Engineering Department of Computer Science and Engineering Coimbatore India Universitat Politècnica de Catalunya BarcelonaTech Departament of Automatic Control Spain

ISBN: (纸本)9798350302493

Existing explainability approaches for convolutional neural networks (CNNs) are mainly applied after training (post-hoc) which is generally unreliable. Ante-hoc explainers trained simultaneously with the CNN are more reliable. However, current ante-hoc explanation methods mainly generate inexplicit concept-based explanations tailored to specific tasks. To address these limitations, we propose a task-agnostic ante-hoc framework that can generate interpretation maps to visually explain any CNN. Our framework simultaneously trains the CNN and a weighting network - an explanation generation module. The generated maps are self-explanatory, eliminating the need for manual identification of concepts. We demonstrate that our method can interpret classification, facial landmark detection, and image captioning tasks. We show that our framework is explicit, faithful, and stable through experiments. To the best of our knowledge, this is the first ante-hoc CNN explanation strategy that produces visual explanations generic to CNNs for different tasks. © 2023 IEEE.

关键词： computer vision

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Ante-Hoc Generation of Task-Agnostic Interpretation Maps

Ante-Hoc Generation of Task-Agnostic Interpretation Maps

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Akash Guna R T Raul Benitez Sikha O K Department of Computer Science and Engineering Amrita School of Engineering Coimbatore India Departament of Automatic Control Universitat Politècnica de Catalunya-BarcelonaTech Spain

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A Haptic Bilateral Robots System for Wrist Rehabilitation after Stroke 14

A Haptic Bilateral Robots System for Wrist Rehabilitation af...

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14th IEEE International Conference on Automation science and Engineering, CASE 2018

作者： López, Erick García Yu, Wen Li, Xiaoou Departament of Automatic Control Mexico Department of Computer Science CINVESTAV-IPN Center for Research and Advanced Studies National Polytechnic Institute Av. IPN 2508 Mexico City07360 Mexico

ISBN: (纸本)9781538635933

Rehabilitation is needed for the patients with upper limb paralysis after a cerebrovascular disease. Many studies showed bilateral rehabilitation system is more effective than unilateral training. In this paper, we use two haptic robots and a visual reality system to design a haptic bilateral rehabilitation system. We propose a novel bilateral control scheme, in which the virtual forces are provided by the interaction in the virtual environment. The interaction through a friendly visual interface during the execution of the training helps to make immersive, entertaining and bearable therapy process. © 2018 IEEE.

关键词： Patient rehabilitation

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Symbolic Regression for Marine Vehicles Identification ∗

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IFAC-PapersOnLine 2015年第16期48卷 210-216页

作者： D. Moreno-Salinas E. Besada-Portas J.A. López-Orozco D. Chaos J.M. de la Cruz J. Aranda Departament of Computer Science and Automatic Control National University Distance Education (UNED) Madrid Spain Department of Computer Architecture and Automatic Control Universidad Complutense de Madrid (UCM) Madrid Spain

The mathematical models used in simulation must be reliable and trustworthy enough to describe the real systems with an appropriate accuracy. This simulation process is specially important in marine environment due to the changing environmental conditions, to the cost of the infrastructure needed to carry out tests, and to the need of calibration, deployment and recovery of the marine systems. If a reliable mathematical model of the vehicle is available, a part of the experimental tests can be avoided. In this paper we present a system identification technique based on genetic programming, the symbolic regression, to be applied on marine systems. In this sense, we show that it is possible to obtain a mathematical model of a ship for control purposes without the need of describing or knowing the model structure in advance, i.e., the identification itself provides the model structure that better describes the system. Thus, we can define a reliable black-box model that is computed in a simple way and where no many experimental data are needed. The model obtained is tested with additional data and manoeuvres to show its good performance and prediction ability.

关键词： Autonomous vehicles marine systems identification symbolic regression genetic programming

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Full autonomous navigation for an aerial robot using behavior-based control motion and SLAM

Full autonomous navigation for an aerial robot using behavio...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： D. Gómez-Anaya Rodrigo Munguía Edmundo Guerra Antoni Grau Departament of Computer Science Universidad de Guadalajara Mexico Automatic Control Department Technical University of Catalonia UPC Barcelona Spain

This work presents a complete navigation architecture for an autonomous aerial robot. The proposed scheme consist of: i) a low-level controller for establishing the attitude and position of the vehicle, ii) a Simultaneous Localization and Mapping (SLAM) system, based in bearing (angular) measurements, which gives the robot the ability for navigating in unknown environments, and iii) a high-level motion control system which generates online trajectories. The high-level motion control system (MCS), which represents the main contribution of this work, is inspired by the behavior-based control strategies. The MCS takes as input a very high level mission target (e.g. “explore as much as you can”) and generates online trajectories according to the mission, but at the same time minimizing uncertainty in the estimations in order to maintain the integrity of the robot. The proposed architecture is explained for simplified 3DOF dynamics, but it could be extended in a straightforward manner in order to be applied to full dynamics. Several simulations are included in order to show the performance of the proposed scheme.

关键词： Motion control Simultaneous localization and mapping Uncertainty Estimation Navigation Robot kinematics

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROscience 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Image vectorization on modern architectures

Image vectorization on modern architectures

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2013 IEEE 9th International Conference on Intelligent computer Communication and Processing, ICCP 2013

作者： Slusanschi, Emil Lupescu, Grigore Computer Science and Engineering Departament Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania

ISBN: (纸本)9781479914937

This work presents an image vectorization application aimed to exploit features found in most of today's modern architectures. Design decisions supported by performance results are presented along with use cases for the proposed solution. We will present the algorithm, the target architectures and threading models, as well as a number of optimization techniques. Finally results of both low power SoC and high performance multicore processors are discussed. © 2013 IEEE.

关键词： System-on-chip

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Image vectorization on modern architectures

Image vectorization on modern architectures

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IEEE International Conference on Intelligent computer Communication and Processing

作者： Emil Slusanschi Grigore Lupescu Computer Science and Engineering Departament Faculty of Automatic Control and Computers University "Politehnica" of Bucharest

ISBN: (纸本)9781479914920

关键词： Vectorization Heterogeneous Manycore Imaging Parallelism Multicore

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A comparison of particle swarm optimization and differential ant stigmergy algorithm

A comparison of particle swarm optimization and differential...

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2012 16th International Conference on System Theory, control and Computing, ICSTCC 2012

作者： Şerbencu, A.E. Şerbencu, A. Control Systems and Electrical Engineering Departament Automatic Computer Science Electrical and Electronic Engineering Faculty Dunarea de Jos University of Galati Romania

ISBN: (纸本)9786068348483

Differential Ant Stigmergy Algorithm (DASA) is a recent meta-heuristic method which represents an adaptation of Ant Colony Optimization (ACO) to continuous optimization problems. Other adaptations of ACO to continuous optimization exist but DASA seems to be very efficient for the class of highdimension real-parameters optimization problems, becoming a competitor to more classical methods such as Particle Swarm Optimization (PSO). The PSO is a meta-heuristic which is also inspired from insects' life as ACO. Even both methods use a population of entities, the memory of PSO is larger as those of DASA. DASA uses just one current solution around which the population search and the difference that generated last improvement. PSO stores the previous best position and velocity of every particle. This paper attempts to examine if an elitist version of DASA has at least the same effectiveness (finding the true global solution) as PSO, but with significantly better efficiency (less function evaluation). The performance comparison of DASA and PSO is implemented using a set of six test functions well known for their difficulty. © 2012 Dunarea de Jos University.

关键词： Ant colony optimization

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A comparison of particle swarm optimization and differential ant stigmergy algorithm

A comparison of particle swarm optimization and differential...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： A. E. Şerbencu A. Şerbencu Control Systems and Electrical Engineering Departament Automatic Computer Science Electrical and Electronic Engineering Faculty Dunãrea de Jos Galati University Romania

关键词： Sociology Statistics Convergence Particle swarm optimization Benchmark testing Vectors Algorithm design and analysis

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