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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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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 distributed control strategy for a hybrid electric vehicle

A distributed control strategy for a hybrid electric vehicle

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

作者： Cezar, Babici Leandru Corneliu Onea, Alexandru Automatic Control and Applied Informatics Departament Gheorghe Asachi Technical University of Iasi Faculty of Automatic Control and Computer Engineering Str. Prof. dr. doc. D. Mangeron nr. 27 700050 Iasi Romania

ISBN: (纸本)9786068348483

This paper describes a distributed control strategy for a hybrid electric vehicle, in order to reduce the fuel consumption, and to maintain a reasonable state of charge (SOC), at the end of the drive cycle. The vehicle is like a system built from control nodes, every one of them having the same priority. The control laws are based on the dc-bus signaling, such way that every source of power (control node) is entering or leaving the network (dc-bus) depending on the voltage thresholds. The algorithm was tested using Matlab Simulink and ADVISOR interface. The results include statistical comparisons of the standard drive cycles using default model and the modified control strategy. © 2012 Dunarea de Jos University.

关键词： Hybrid vehicles

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A distributed control strategy for a hybrid electric vehicle

A distributed control strategy for a hybrid electric vehicle

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

作者： Babici Leandru Corneliu Cezar Alexandru Onea Automatic Control and Applied Informatics Departament Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University of Iasi Iasi Romania

关键词： Batteries Hybrid electric vehicles Fuels Supercapacitors Torque System-on-a-chip

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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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A rule-based energy management strategy for parallel hybrid vehicles with supercapacitors

A rule-based energy management strategy for parallel hybrid ...

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15th International Conference on System Theory, control and Computing, ICSTCC 2011

作者： Cezar, Babici Onea, Alexandru Automatic Control and Applied Informatics Departament Gheorghe Asachi Technical University Iasi Faculty of Automatic Control and Computer Engineering Str. Prof. dr. doc. D. Mangeron nr. 27 700050 Iasi Romania

ISBN: (纸本)9781457711732

In order to improve the lifetime and performance of a hybrid electric vehicle, one of the most challenging tasks is to improve the performance of the electrical energy storage, regarding the electrical power and energy capacity. By introducing a supercapacitor as auxiliary source to increase the system power and to take over the battery stresses, the performance of the combined energy storage unit is improved. This paper introduces a completed model of energy storage system, including a pack of batteries, a pack of supercapacitors and a control strategy. The aim is to discharge the capacitors when the required power from energy storage is above a threshold meaning that the driver needs a boost of power for a period of time. Because of their high density of power supercapacitors have more efficiency in delivering it for short time. This has a positive impact on the fuel consumption and the state of charge at the end of the drive cycle. © 2011 Faculty of Auto control.

关键词： Supercapacitor

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