The Experts below are selected from a list of 174 Experts worldwide ranked by ideXlab platform
A Jimenezfernandez - One of the best experts on this subject based on the ideXlab platform.
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performance study of software aer based convolutions on a parallel supercomputer
International Conference on Artificial Neural Networks, 2011Co-Authors: Rafael J Monterogonzalez, Arturo Morgadoestevez, A Linaresbarranco, B Linaresbarranco, Fernando Perezpena, J A Perezcarrasco, A JimenezfernandezAbstract:This paper is based on the simulation of a convolution model for bioinspired neuromorphic systems using the Address-Event-Representation (AER) philosophy and implemented in the supercomputer CRS of the University of Cadiz (UCA). In this work we improve the runtime of the simulation, by dividing an image into smaller parts before AER convolution and running each operation in a node of the cluster. This research involves a test cases design in which the optimal parameters are set to run the AER convolution in parallel processors. These cases consist on running the convolution taking an image divided in different number of parts, applying to each part a Sobel Filter for edge detection, and based on the AER-TOOL simulator. Execution times are compared for all cases and the optimal configuration of the system is discussed. In general, CRS obtain better performances when the image is divided than for the whole image.
Rafael J Monterogonzalez - One of the best experts on this subject based on the ideXlab platform.
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performance study of software aer based convolutions on a parallel supercomputer
International Conference on Artificial Neural Networks, 2011Co-Authors: Rafael J Monterogonzalez, Arturo Morgadoestevez, A Linaresbarranco, B Linaresbarranco, Fernando Perezpena, J A Perezcarrasco, A JimenezfernandezAbstract:This paper is based on the simulation of a convolution model for bioinspired neuromorphic systems using the Address-Event-Representation (AER) philosophy and implemented in the supercomputer CRS of the University of Cadiz (UCA). In this work we improve the runtime of the simulation, by dividing an image into smaller parts before AER convolution and running each operation in a node of the cluster. This research involves a test cases design in which the optimal parameters are set to run the AER convolution in parallel processors. These cases consist on running the convolution taking an image divided in different number of parts, applying to each part a Sobel Filter for edge detection, and based on the AER-TOOL simulator. Execution times are compared for all cases and the optimal configuration of the system is discussed. In general, CRS obtain better performances when the image is divided than for the whole image.
W. Głowacz - One of the best experts on this subject based on the ideXlab platform.
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Shape Recognition of Film Sequence with Application of Sobel Filter and Backpropagation Neural Network
Human-Computer Systems Interaction, 2009Co-Authors: Adam Glowacz, W. GłowaczAbstract:A new approach to shape recognition is presented. This approach is based on Sobel Filter and backpropagation neural network. Investigations of the shape recognition were carried out for film sequences. The aim of this paper is analysis of a system which enables shape recognition.
A Linaresbarranco - One of the best experts on this subject based on the ideXlab platform.
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performance study of software aer based convolutions on a parallel supercomputer
International Conference on Artificial Neural Networks, 2011Co-Authors: Rafael J Monterogonzalez, Arturo Morgadoestevez, A Linaresbarranco, B Linaresbarranco, Fernando Perezpena, J A Perezcarrasco, A JimenezfernandezAbstract:This paper is based on the simulation of a convolution model for bioinspired neuromorphic systems using the Address-Event-Representation (AER) philosophy and implemented in the supercomputer CRS of the University of Cadiz (UCA). In this work we improve the runtime of the simulation, by dividing an image into smaller parts before AER convolution and running each operation in a node of the cluster. This research involves a test cases design in which the optimal parameters are set to run the AER convolution in parallel processors. These cases consist on running the convolution taking an image divided in different number of parts, applying to each part a Sobel Filter for edge detection, and based on the AER-TOOL simulator. Execution times are compared for all cases and the optimal configuration of the system is discussed. In general, CRS obtain better performances when the image is divided than for the whole image.
Fernando Perezpena - One of the best experts on this subject based on the ideXlab platform.
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performance study of software aer based convolutions on a parallel supercomputer
International Conference on Artificial Neural Networks, 2011Co-Authors: Rafael J Monterogonzalez, Arturo Morgadoestevez, A Linaresbarranco, B Linaresbarranco, Fernando Perezpena, J A Perezcarrasco, A JimenezfernandezAbstract:This paper is based on the simulation of a convolution model for bioinspired neuromorphic systems using the Address-Event-Representation (AER) philosophy and implemented in the supercomputer CRS of the University of Cadiz (UCA). In this work we improve the runtime of the simulation, by dividing an image into smaller parts before AER convolution and running each operation in a node of the cluster. This research involves a test cases design in which the optimal parameters are set to run the AER convolution in parallel processors. These cases consist on running the convolution taking an image divided in different number of parts, applying to each part a Sobel Filter for edge detection, and based on the AER-TOOL simulator. Execution times are compared for all cases and the optimal configuration of the system is discussed. In general, CRS obtain better performances when the image is divided than for the whole image.