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Advances in Computational Intelligence: 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, Gran Canaria, Spain, June 12-14, 2019, Proceedings, Part II 2019 ed. [Mīkstie vāki]

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  • Formāts: Paperback / softback, 926 pages, height x width: 235x155 mm, weight: 1436 g, 306 Illustrations, color; 211 Illustrations, black and white; XXX, 926 p. 517 illus., 306 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 11507
  • Izdošanas datums: 16-May-2019
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030205177
  • ISBN-13: 9783030205171
  • Mīkstie vāki
  • Cena: 91,53 €*
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  • Formāts: Paperback / softback, 926 pages, height x width: 235x155 mm, weight: 1436 g, 306 Illustrations, color; 211 Illustrations, black and white; XXX, 926 p. 517 illus., 306 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 11507
  • Izdošanas datums: 16-May-2019
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030205177
  • ISBN-13: 9783030205171

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.

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.