Artificial Neural Networks in Pattern Recognition: 5th Inns Iapr Tc 3 Girpr Workshop, Annpr 2012, Trento, Italy, September 17-19, 2012, Proceedings

Learning Algorithms.- How to Quantitatively Compare Data Dissimilarities for Unsupervised Machine Learning?- Kernel Robust Soft Learning Vector Quantization.- Incremental Learning by Message Passing in Hierarchical Temporal.- Representative Prototype Sets for Data Characterization and Classification.- Feature Selection by Block Addition and Block Deletion.- Gradient Algorithms for Exploration/Exploitation Trade-Offs: Global and Local Variants.- Towards a Novel Probabilistic Graphical Model of Sequential Data: Fundamental Notions and a Solution to the Problem of Parameter Learning.- Towards a Novel Probabilistic Graphical Model of Sequential Data: A Solution to the Problem of Structure Learning and an Empirical Evaluation.- Statistical Recognition of a Set of Patterns Using Novel Probability Neural Network.- On Graph-Associated Matrices and Their Eigenvalues for Optical Character Recognition.- Classification of Segmented Objects through a Multi-net Approach.- On Instance Selection in Audio Based Emotion Recognition.- Grayscale Images and RGB Video: Compression by Morphological Neural Network.- NeuCube EvoSpike Architecture for Spatio-temporal Modelling and Pattern Recognition of Brain Signals.

• Format: Paperback
• Language: English
• ISBN: 3642332110
• ISBN13: 9783642332111
• Release Date: August 2012
• Publisher: Springer
• Length: 245 Pages
• Weight: 0.80 lbs.
• Dimensions: 0.5" x 6.1" x 9.2"