Advances in Neural Computation, Machine Learning, and Cognitive Research III: Selected Papers from the XXI International Conference on Neuroinformatics, October 7-11, 2019, Dolgoprudny, Moscow Region, Russia: Studies in Computational Intelligence, cartea 856
Editat de Boris Kryzhanovsky, Witali Dunin-Barkowski, Vladimir Redko, Yury Tiumentseven Limba Engleză Paperback – 5 sep 2020
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Specificații
ISBN-13: 9783030304270
ISBN-10: 3030304272
Pagini: 428
Ilustrații: XVII, 428 p. 210 illus., 120 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.62 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 3030304272
Pagini: 428
Ilustrații: XVII, 428 p. 210 illus., 120 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.62 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Cham, Switzerland
Cuprins
Preface.- Part I: Invited Papers.- Chapter 1. Deep Learning a Single Photo Voxel Model Prediction from Real and Synthetic Images.- Chapter 2. Tensor Train Neural Networks in Retail Operations.- Chapter 3. Semi-Empirical Neural Network Based Modeling and Identification of Controlled Dynamical Systems, etc.
Textul de pe ultima copertă
This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large scale neural models, brain computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXI International Conference on Neuroinformatics, held on October 7-11, 2019, in Dolgoprudny, a town in Moscow region, Russia.
Caracteristici
Reports on advanced theories and applications of artificial neural networks Focuses on problems in neuroscience, systems biophysics, cognitive research and adaptive control Merges topics in neurobiology, machine learning and evolutionary programming