Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning

Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning
Author :
Publisher : Springer Nature
Total Pages : 818
Release :
ISBN-10 : 9783030304843
ISBN-13 : 3030304841
Rating : 4/5 (43 Downloads)

Synopsis Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning by : Igor V. Tetko

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions

Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions
Author :
Publisher : Springer Nature
Total Pages : 872
Release :
ISBN-10 : 9783030304935
ISBN-13 : 3030304930
Rating : 4/5 (35 Downloads)

Synopsis Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions by : Igor V. Tetko

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series

Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series
Author :
Publisher : Springer Nature
Total Pages : 775
Release :
ISBN-10 : 9783030304904
ISBN-13 : 3030304906
Rating : 4/5 (04 Downloads)

Synopsis Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series by : Igor V. Tetko

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation

Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation
Author :
Publisher : Springer Nature
Total Pages : 848
Release :
ISBN-10 : 9783030304874
ISBN-13 : 3030304876
Rating : 4/5 (74 Downloads)

Synopsis Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation by : Igor V. Tetko

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing

Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing
Author :
Publisher : Springer Nature
Total Pages : 749
Release :
ISBN-10 : 9783030305086
ISBN-13 : 3030305082
Rating : 4/5 (86 Downloads)

Synopsis Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing by : Igor V. Tetko

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning

Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning
Author :
Publisher :
Total Pages : 807
Release :
ISBN-10 : 303030485X
ISBN-13 : 9783030304850
Rating : 4/5 (5X Downloads)

Synopsis Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning by : Igor V. Tetko

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Artificial Neural Networks and Machine Learning – ICANN 2018

Artificial Neural Networks and Machine Learning – ICANN 2018
Author :
Publisher : Springer
Total Pages : 866
Release :
ISBN-10 : 9783030014247
ISBN-13 : 303001424X
Rating : 4/5 (47 Downloads)

Synopsis Artificial Neural Networks and Machine Learning – ICANN 2018 by : Věra Kůrková

This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning.

Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series

Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series
Author :
Publisher :
Total Pages : 761
Release :
ISBN-10 : 3030304914
ISBN-13 : 9783030304911
Rating : 4/5 (14 Downloads)

Synopsis Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series by : Igor V. Tetko

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation

Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation
Author :
Publisher :
Total Pages :
Release :
ISBN-10 : 3030304884
ISBN-13 : 9783030304881
Rating : 4/5 (84 Downloads)

Synopsis Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation by : Igor V. Tetko

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Artificial Neural Networks and Machine Learning – ICANN 2020

Artificial Neural Networks and Machine Learning – ICANN 2020
Author :
Publisher : Springer Nature
Total Pages : 891
Release :
ISBN-10 : 9783030616168
ISBN-13 : 3030616169
Rating : 4/5 (68 Downloads)

Synopsis Artificial Neural Networks and Machine Learning – ICANN 2020 by : Igor Farkaš

The proceedings set LNCS 12396 and 12397 constitute the proceedings of the 29th International Conference on Artificial Neural Networks, ICANN 2020, held in Bratislava, Slovakia, in September 2020.* The total of 139 full papers presented in these proceedings was carefully reviewed and selected from 249 submissions. They were organized in 2 volumes focusing on topics such as adversarial machine learning, bioinformatics and biosignal analysis, cognitive models, neural network theory and information theoretic learning, and robotics and neural models of perception and action. *The conference was postponed to 2021 due to the COVID-19 pandemic.