LEADER 05835nam 22008175 450 001 996466244203316 005 20230317132455.0 010 $a3-319-46182-6 024 7 $a10.1007/978-3-319-46182-3 035 $a(CKB)3710000000872932 035 $a(DE-He213)978-3-319-46182-3 035 $a(MiAaPQ)EBC6285707 035 $a(MiAaPQ)EBC5610849 035 $a(Au-PeEL)EBL5610849 035 $a(OCoLC)958639872 035 $a(PPN)195511069 035 $a(EXLCZ)993710000000872932 100 $a20160908d2016 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Neural Networks in Pattern Recognition$b[electronic resource] $e7th IAPR TC3 Workshop, ANNPR 2016, Ulm, Germany, September 28?30, 2016, Proceedings /$fedited by Friedhelm Schwenker, Hazem M. Abbas, Neamat El Gayar, Edmondo Trentin 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (XI, 335 p. 107 illus.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v9896 300 $aIncludes index. 311 $a3-319-46181-8 327 $aLearning 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. . 330 $aThis book constitutes the refereed proceedings of the 7th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2016, held in Ulm, Germany, in September 2016. The 25 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 32 submissions for inclusion in this volume. The workshop will act as a major forum for international researchers and practitioners working in all areas of neural network- and machine learning-based pattern recognition to present and discuss the latest research, results, and ideas in these areas. . 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v9896 606 $aArtificial intelligence 606 $aPattern recognition systems 606 $aData mining 606 $aComputer vision 606 $aUser interfaces (Computer systems) 606 $aHuman-computer interaction 606 $aComputer science 606 $aArtificial Intelligence 606 $aAutomated Pattern Recognition 606 $aData Mining and Knowledge Discovery 606 $aComputer Vision 606 $aUser Interfaces and Human Computer Interaction 606 $aTheory of Computation 615 0$aArtificial intelligence. 615 0$aPattern recognition systems. 615 0$aData mining. 615 0$aComputer vision. 615 0$aUser interfaces (Computer systems). 615 0$aHuman-computer interaction. 615 0$aComputer science. 615 14$aArtificial Intelligence. 615 24$aAutomated Pattern Recognition. 615 24$aData Mining and Knowledge Discovery. 615 24$aComputer Vision. 615 24$aUser Interfaces and Human Computer Interaction. 615 24$aTheory of Computation. 676 $a006.32 702 $aSchwenker$b Friedhelm$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAbbas$b Hazem M$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aEl Gayar$b Neamat$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTrentin$b Edmondo$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466244203316 996 $aArtificial Neural Networks in Pattern Recognition$92968246 997 $aUNISA