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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(2)
IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - IES 2014: 2014 IEEE Symposium on Intelligent Embedded Systems, Proceedings(1)
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scopus(8)
A self-organizing map for traffic flow monitoring
Conference ObjectAbstract: Most of object detection algorithms do not yield perfect foreground segmentation masks. These errorsPalabras claves:object detection, postprocessing techniques, Self-organizing neural networks, Surveillance systems, traffic monitoringAutores:Domínguez E., Esteban José Palomo, Jerez-Aragonés J.M., López-Rubio E., Luque-Baena R.M.Fuentes:scopusAddressing critical issues in the development of an Oncology Information System
ArticleAbstract: Purposes: This paper presents the experience on the design and implementation of a user-centered OncPalabras claves:Biomedical Applications, electronic health record, Oncology Information System, survival analysisAutores:Alba E., Franco L., Jerez-Aragonés J.M., José Luis Subirats, Ribelles N., Urda D.Fuentes:scopusFPGA Hardware Acceleration of Monte Carlo Simulations for the Ising Model
ArticleAbstract: A two-dimensional Ising model with nearest-neighbors ferromagnetic interactions is implemented in aPalabras claves:Hardware implementation, Ising model, LFSR random number generator, Monte Carlo simulationsAutores:Cannas S.A., Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., Montemurro M.A.Fuentes:scopusFPGA Implementation of Neurocomputational Models: Comparison Between Standard Back-Propagation and C-Mantec Constructive Algorithm
ArticleAbstract: Recent advances in FPGA technology have permitted the implementation of neurocomputational models, mPalabras claves:Constructive Neural Networks, Fpga, Hardware implementationAutores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., Juárez G.E.Fuentes:scopusFPGA implementation comparison between C-mantec and back-propagation neural network algorithms
Conference ObjectAbstract: Recent advances in FPGA technology have permitted the implementation of neurocomputational models, mPalabras claves:Constructive Neural Networks, Fpga, Hardware implementationAutores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., Juárez G.E.Fuentes:scopusFPGA implementation of the c-mantec neural network constructive algorithm
ArticleAbstract: Competitive majority network trained by error correction (C-Mantec), a recently proposed constructivPalabras claves:Circuit complexity, constructive neural networks (CoNN), on-chip learning, Threshold networksAutores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M.Fuentes:scopusHigh precision FPGA implementation of neural network activation functions
Conference ObjectAbstract: The efficient implementation of artificial neural networks in FPGA boards requires tackling severalPalabras claves:Autores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., Juárez G.E., Perez J.O.Fuentes:scopusLayer multiplexing FPGA implementation for deep back-propagation learning
ArticleAbstract: Training of large scale neural networks, like those used nowadays in Deep Learning schemes, requiresPalabras claves:Deep Neural Networks, Fpga, Hardware implementation, Layer multiplexing, Supervised learningAutores:Francisco Ortega-Zamorano, Franco L., Gómez I., Jerez-Aragonés J.M.Fuentes:scopus