Artificial neural networks for pattern recognition.  7th IAPR TC3 Workshop, ANNPR 2016, Ulm, Germany, September 28-30, 2016, Proceedings /  
 ANNPR 2016 
Friedhelm Schwenker, Hazem M. Abbas, Neamat El Gayar, Edmondo Trentin (eds.). 
 - xi, 335 pages :  illustrations.  24 cm. 
<br/><br/> Includes author index.<br/>  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- 
<br/><br/>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 --  
<br/><br/><label>ISBN: </label>9783319461816 
<br/><br/><label>LCCN: </label>2016950420 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Neural networks (Computer science)<br/>Pattern recognition systems--Congresses
<br/><br/><label>Dewey Class. No.: </label>006.32