UID:
almahu_9948105344302882
Umfang:
XXX, 926 p. 517 illus., 306 illus. in color.
,
online resource.
ISBN:
9783030205188
Serie:
Theoretical Computer Science and General Issues ; 11507
Inhalt:
This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, held at Gran Canaria, Spain, in June 2019. The 150 revised full papers presented in this two-volume set were carefully reviewed and selected from 210 submissions. The papers are organized in topical sections on machine learning in weather observation and forecasting; computational intelligence methods for time series; human activity recognition; new and future tendencies in brain-computer interface systems; random-weights neural networks; pattern recognition; deep learning and natural language processing; software testing and intelligent systems; data-driven intelligent transportation systems; deep learning models in healthcare and biomedicine; deep learning beyond convolution; artificial neural network for biomedical image processing; machine learning in vision and robotics; system identification, process control, and manufacturing; image and signal processing; soft computing; mathematics for neural networks; internet modeling, communication and networking; expert systems; evolutionary and genetic algorithms; advances in computational intelligence; computational biology and bioinformatics.
Anmerkung:
Deep learning beyond convolution -- Artificial neural network for biomedical image processing -- Machine learning in vision and robotics -- System identification, process control, and manufacturing -- Image and signal processing -- Soft computing -- Mathematics for neural networks -- Internet modeling, communication and networking -- Expert systems -- Evolutionary and genetic algorithms -- Advances in computational intelligence -- Computational biology and bioinformatics.
In:
Springer eBooks
Weitere Ausg.:
Printed edition: ISBN 9783030205171
Weitere Ausg.:
Printed edition: ISBN 9783030205195
Sprache:
Englisch
DOI:
10.1007/978-3-030-20518-8
URL:
https://doi.org/10.1007/978-3-030-20518-8
