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Artificial neural networks for pattern recognition. 7th IAPR TC3 Workshop, ANNPR 2016, Ulm, Germany, September 28-30, 2016, Proceedings / Friedhelm Schwenker, Hazem M. Abbas, Neamat El Gayar, Edmondo Trentin (eds.).

Von: ANNPR (Workshop) Ulm, Germany) 2016.
Mitwirkende(r): Schwenker,Friedhelm | Abbas, Hazem M | El Gayar, Neamat | Trentin, Edmondo.
Materialtyp: materialTypeLabelBuchVerlag: New York, NY : Springer Berlin Heidelberg, 2016.Beschreibung: xi, 335 pages : illustrations. 24 cm.Inhaltstyp: text Medientyp: unmediated Datenträgertyp: volumeISBN: 9783319461816.Weitere Titel: ANNPR 2016.Schlagwörter: Neural networks (Computer science) | Pattern recognition systems -- CongressesDDC-Klassifikation: 006.32 Online-Ressourcen: Publisher description | Table of contents only
Inhalte:
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 --
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Books Books 6october
1105
معرض الكتاب2018 006.32 S A (Regal durchstöbern) 1 Verfügbar

Includes author index.

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 --

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