Mostrando 10 resultados de: 26
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(6)
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scopus(26)
A New Self-Organizing Neural Gas Model based on Bregman Divergences
Conference ObjectAbstract: In this paper, a new self-organizing neural gas model that we call Growing Hierarchical Bregman NeurPalabras claves:Autores:Esteban José Palomo, López-Rubio E., Luque-Baena R.M., Molina-Cabello M.A.Fuentes:scopusA Novel Continual Learning Approach for Competitive Neural Networks
Conference ObjectAbstract: Continual learning tries to address the stability-plasticity dilemma to avoid catastrophic forgettinPalabras claves:Competitive neural networks, Continual learning, unsupervised learningAutores:Esteban José Palomo, Fernández-Rodríguez J.D., López-Rubio E., Maza-Quiroga R.M., Ortiz-de-Lazcano-Lobato J.M.Fuentes:scopusA competitive neural network for multiple object tracking in video sequence analysis
Conference ObjectAbstract: Tracking of moving objects in real situation is a challenging research issue, due to dynamic changesPalabras claves:feature selection, Feature weigthing, Genetic Algorithms, Growing competitive neural networks, Multiple object trackingAutores:Domínguez E., Esteban José Palomo, López-Rubio E., Luque-Baena R.M., Ortiz-de-Lazcano-Lobato J.M.Fuentes:scopusAssessment of geometric features for individual identification and verification in biometric hand systems
ArticleAbstract: This paper studies the reliability of geometric features for the identification of users based on haPalabras claves:Genetic Algorithms, Geometric features, Hand biometrics, User identificationAutores:Elizondo D., Esteban José Palomo, López-Rubio E., Luque-Baena R.M., Watson T.Fuentes:scopusBregman divergences for growing hierarchical self-organizing networks
ArticleAbstract: Growing hierarchical self-organizing models are characterized by the flexibility of their structure,Palabras claves:Bregman divergences, classification, self organization, VisualizationAutores:Domínguez E., Esteban José Palomo, López-Rubio E.Fuentes:scopusDeep learning-based anomalous object detection system for panoramic cameras managed by a Jetson TX2 board
Conference ObjectAbstract: Social conflicts appearing in the media are increasing public awareness about security issues, resulPalabras claves:deep learning, panoramic cameras, Power saving, video surveillanceAutores:Benito-Picazo J., Domínguez E., Esteban José Palomo, López-Rubio E., Ramos-Jimenez G.Fuentes:scopusDeep learning-based anomalous object detection system powered by microcontroller for PTZ cameras
Conference ObjectAbstract: Automatic video surveillance systems are usually designed to detect anomalous objects being presentPalabras claves:Convolutional neural network, feed forward neural network, foreground detection, PTZ cameraAutores:Benito-Picazo J., Domínguez E., Esteban José Palomo, López-Rubio E., Ortiz-de-Lazcano-Lobato J.M.Fuentes:scopusDeep learning-based video surveillance system managed by low cost hardware and panoramic cameras
ArticleAbstract: The design of automated video surveillance systems often involves the detection of agents which exhiPalabras claves:Convolutional neural network, feed forward neural network, foreground detection, panoramic cameraAutores:Benito-Picazo J., Domínguez E., Esteban José Palomo, López-Rubio E.Fuentes:scopusDynamic topology learning with the probabilistic self-organizing graph
ArticleAbstract: Self-organizing neural networks are usually focused on prototype learning, while the topology is helPalabras claves:classification, Image quantization, image segmentation, Self-Organization, unsupervised learning, VisualizationAutores:Carmen Vargas-González M., Esteban José Palomo, López-Rubio E., Miguel Ortiz-de-Lazcano-Lobato J.Fuentes:scopusDynamic tree topology learning by self-organization
ArticleAbstract: The discovery of the underlying topology of real-world data is a difficult task due to the high-dimePalabras claves:Computer Vision, Self-organizing map topologies, Spanning trees, unsupervised learningAutores:Domínguez E., Esteban José Palomo, López-Rubio E., Luque-Baena R.M.Fuentes:scopus