Artificial Neural Networks in Pattern Recognition: 7th IAPR TC3 Workshop, ANNPR 2016, Ulm, Germany, September 28-30, 2016, Proceedings - Tapa blanda

Sinopsis

Learning sequential data with the help of linear systems.- A spiking neural network for personalised modelling of Electrogastogrophy (EGG).- Improving generalization abilities of maximal average margin classifiers.- Finding small sets of random Fourier features for shift-invariant kernel approximation.- Incremental construction of low-dimensional data representations.- Soft-constrained nonparametric density estimation with artificial neural networks.- Density based clustering via dominant sets.- Co-training with credal models.- Interpretable classifiers in precision medicine: feature selection and multi-class categorization.- On the evaluation of tensor-based representations for optimum-pathforest classification.- On the harmony search using quaternions.- Learning parameters in deep belief networks through firefly algorithm.- Towards effective classification of imbalanced data with convolutional neural networks.- On CPU performance optimization of restricted Boltzmann machine and convolutional RBM.- Comparing incremental learning strategies for convolutional neural networks.- Approximation of graph edit distance by means of a utility matrix.- Time series classification in reservoir- and model-space: a comparison.- Objectness scoring and detection proposals in forward-Looking sonar images with convolutional neural networks.- Background categorization for automatic animal detection in aerial videos using neural networks.- Predictive segmentation using multichannel neural networks in Arabic OCR system.- Quad-tree based image segmentation and feature extraction to recognize online handwritten Bangla characters.- A hybrid recurrent neural network/dynamic probabilistic graphical model predictor of the disulfide bonding state of cysteines from the primary structure of proteins.- Using radial basis function neural networks for continuous anddiscrete pain estimation from bio-physiological signals.- Active learning for speech event detection in HCI.- Emotion recognition in speech with deep learning architectures.- On gestures and postural behavior as a modality in ensemble methods.- Machine learning driven heart rate detection with camera photoplethysmography in time domain. 

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