CIENCIA DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL

Département

Entropy-based incremental variational bayes learning of gaussian mixtures
IEEE Transactions on Neural Networks and Learning Systems, Vol. 23, Núm. 3, pp. 534-540

Entropy-based variational scheme for fast bayes learning of gaussian mixtures
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Learning Gaussian mixture models with entropy-based criteria
IEEE Transactions on Neural Networks, Vol. 20, Núm. 11, pp. 1756-1771

Clustering EBEM: modelos de mezclas gausianas basados en maximización de entropía
Clustering EBEM: modelos de mezclas gausianas basados en maximización de entropía

Color image segmentation through unsupervised Gaussian mixture models
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EBEM: An entropy-based em algorithm for Gaussian mixture models
Proceedings - International Conference on Pattern Recognition
Two entropy-based methods for learning unsupervised Gaussian mixture models
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

First steps towards stereo-based 6DOF SLAM for the visually impaired
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

An entropy maximization approach to optimal model selection in gaussian mixtures
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2905, pp. 432-439
Compact mapping in plane-parallel environments using stereo vision
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2905, pp. 659-666