Advances in Neural Networks – ISNN 2019
Advances in Neural Networks – ISNN 2019

Author: Huchuan Lu

Publisher: Springer

Published: 2019-06-26

Total Pages: 499

ISBN-13: 3030227960

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This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019. The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.

Advances in Neural Networks – ISNN 2020
Advances in Neural Networks – ISNN 2020

Author: Min Han

Publisher: Springer Nature

Published: 2020-11-28

Total Pages: 284

ISBN-13: 3030642216

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This volume LNCS 12557 constitutes the refereed proceedings of the 17th International Symposium on Neural Networks, ISNN 2020, held in Cairo, Egypt, in December 2020. The 24 papers presented in the two volumes were carefully reviewed and selected from 39 submissions. The papers were organized in topical sections named: optimization algorithms; neurodynamics, complex systems, and chaos; supervised/unsupervised/reinforcement learning/deep learning; models, methods and algorithms; and signal, image and video processing.

Advances in Neural Networks – ISNN 2019
Advances in Neural Networks – ISNN 2019

Author: Huchuan Lu

Publisher: Springer

Published: 2019-06-26

Total Pages: 630

ISBN-13: 3030228088

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This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019. The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.

Advances in Computational Intelligence
Advances in Computational Intelligence

Author: Ignacio Rojas

Publisher: Springer

Published: 2019-06-05

Total Pages: 938

ISBN-13: 3030205185

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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.

Advances in Neural Networks - ISNN 2019
Advances in Neural Networks - ISNN 2019

Author: Huchuan Lu

Publisher:

Published: 2019

Total Pages: 615

ISBN-13: 9783030228095

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This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019. The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.

Advanced AI Methods for Plant Disease and Pest Recognition
Advanced AI Methods for Plant Disease and Pest Recognition

Author: Jucheng Yang

Publisher: Frontiers Media SA

Published: 2024-06-06

Total Pages: 350

ISBN-13: 2832550096

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Plant diseases and pests cause significant losses to farmers and threaten food security worldwide. Monitoring the growing conditions of crops and detecting plant diseases is critical for sustainable agriculture. Traditionally, crop inspection has been carried out by people with expert knowledge in the field. However, regarding any activity carried out by humans, this activity is prone to errors, leading to possible incorrect decisions. Innovation is, therefore, an essential fact of modern agriculture. In this context, deep learning has played a key role in solving complicated applications with increasing accuracy over time, and recent interest in this type of technology has prompted its potential application to address complex problems in agriculture, such as plant disease and pest recognition. Although substantial progress has been made in the area, several challenges still remain, especially those that limit systems to operate in real-world scenarios.

Applications of Artificial Neural Networks for Nonlinear Data
Applications of Artificial Neural Networks for Nonlinear Data

Author: Patel, Hiral Ashil

Publisher: IGI Global

Published: 2020-09-25

Total Pages: 315

ISBN-13: 1799840433

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Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.

Research Anthology on Artificial Neural Network Applications
Research Anthology on Artificial Neural Network Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2021-07-16

Total Pages: 1575

ISBN-13: 1668424096

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Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.