Artificial Neural Networks in Pattern Recognition : 7th IAPR TC3 Workshop, ANNPR 2016, Ulm, Germany, September 28-30, 2016, Proceedings / edited by Friedhelm Schwenker, Hazem M. Abbas, Neamat El Gayar, Edmondo Trentin.

Format:

Book

Contributor:

Schwenker, Friedhelm, editor.

Abbas, Hazem M., editor.

El Gayar, Neamat, editor.

Trentin, Edmondo, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 9896.

Lecture Notes in Artificial Intelligence ; 9896

Language:

English

Subjects (All):

Artificial intelligence.

Pattern perception.

Data mining.

Optical data processing.

User interfaces (Computer systems).

Computers.

Artificial Intelligence.

Pattern Recognition.

Data Mining and Knowledge Discovery.

Image Processing and Computer Vision.

User Interfaces and Human Computer Interaction.

Computation by Abstract Devices.

Local Subjects:

Artificial Intelligence.

Pattern Recognition.

Data Mining and Knowledge Discovery.

Image Processing and Computer Vision.

User Interfaces and Human Computer Interaction.

Computation by Abstract Devices.

Physical Description:

1 online resource (XI, 335 pages) : 107 illustrations.

Edition:

First edition 2016.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

System Details:

text file PDF

Summary:

This 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. .

Contents:

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. .

Other Format:

Printed edition:

ISBN:

978-3-319-46182-3

9783319461823

Access Restriction:

Restricted for use by site license.