Format:
1 Online-Ressource (XXX, 940 p. 394 illus., 262 illus. in color)
Edition:
1st ed. 2019
ISBN:
9783030205218
Series Statement:
Theoretical Computer Science and General Issues 11506
Content:
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
Content:
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
Additional Edition:
ISBN 9783030205201
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 978-3-030-20520-1
Language:
English
DOI:
10.1007/978-3-030-20521-8
