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Special Issue Neural Networks
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Book Synopsis Generative Adversarial Learning: Architectures and Applications by : Roozbeh Razavi-Far
Download or read book Generative Adversarial Learning: Architectures and Applications written by Roozbeh Razavi-Far and published by Springer Nature. This book was released on 2022-03-11 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs’ theoretical developments and their applications.
Book Synopsis Learning-Based Control by : Zhong-Ping Jiang
Download or read book Learning-Based Control written by Zhong-Ping Jiang and published by Now Publishers. This book was released on 2020-12-07 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent success of Reinforcement Learning and related methods can be attributed to several key factors. First, it is driven by reward signals obtained through the interaction with the environment. Second, it is closely related to the human learning behavior. Third, it has a solid mathematical foundation. Nonetheless, conventional Reinforcement Learning theory exhibits some shortcomings particularly in a continuous environment or in considering the stability and robustness of the controlled process. In this monograph, the authors build on Reinforcement Learning to present a learning-based approach for controlling dynamical systems from real-time data and review some major developments in this relatively young field. In doing so the authors develop a framework for learning-based control theory that shows how to learn directly suboptimal controllers from input-output data. There are three main challenges on the development of learning-based control. First, there is a need to generalize existing recursive methods. Second, as a fundamental difference between learning-based control and Reinforcement Learning, stability and robustness are important issues that must be addressed for the safety-critical engineering systems such as self-driving cars. Third, data efficiency of Reinforcement Learning algorithms need be addressed for safety-critical engineering systems. This monograph provides the reader with an accessible primer on a new direction in control theory still in its infancy, namely Learning-Based Control Theory, that is closely tied to the literature of safe Reinforcement Learning and Adaptive Dynamic Programming.
Book Synopsis Artificial Neural Networks and Evolutionary Computation in Remote Sensing by : Taskin Kavzoglu
Download or read book Artificial Neural Networks and Evolutionary Computation in Remote Sensing written by Taskin Kavzoglu and published by MDPI. This book was released on 2021-01-19 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.
Book Synopsis Special Issue on Neural Networks and Machine Learning by : Sitian Qin
Download or read book Special Issue on Neural Networks and Machine Learning written by Sitian Qin and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Evolutionary Computer Vision by : Gustavo Olague
Download or read book Evolutionary Computer Vision written by Gustavo Olague and published by Springer. This book was released on 2016-09-28 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains the theory and application of evolutionary computer vision, a new paradigm where challenging vision problems can be approached using the techniques of evolutionary computing. This methodology achieves excellent results for defining fitness functions and representations for problems by merging evolutionary computation with mathematical optimization to produce automatic creation of emerging visual behaviors. In the first part of the book the author surveys the literature in concise form, defines the relevant terminology, and offers historical and philosophical motivations for the key research problems in the field. For researchers from the computer vision community, he offers a simple introduction to the evolutionary computing paradigm. The second part of the book focuses on implementing evolutionary algorithms that solve given problems using working programs in the major fields of low-, intermediate- and high-level computer vision. This book will be of value to researchers, engineers, and students in the fields of computer vision, evolutionary computing, robotics, biologically inspired mechatronics, electronics engineering, control, and artificial intelligence.
Book Synopsis Application of Artificial Neural Networks in Geoinformatics by : Saro Lee
Download or read book Application of Artificial Neural Networks in Geoinformatics written by Saro Lee and published by MDPI. This book was released on 2018-04-09 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Application of Artificial Neural Networks in Geoinformatics" that was published in Applied Sciences
Download or read book Federated Learning written by Qiang Yang and published by Springer Nature. This book was released on 2020-11-25 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”
Book Synopsis Advances in Neural Networks Research by : D.C. Wunsch II
Download or read book Advances in Neural Networks Research written by D.C. Wunsch II and published by Elsevier. This book was released on 2003-08-22 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: IJCNN is the flagship conference of the INNS, as well as the IEEE Neural Networks Society. It has arguably been the preeminent conference in the field, even as neural network conferences have proliferated and specialized. As the number of conferences has grown, its strongest competition has migrated away from an emphasis on neural networks. IJCNN has embraced the proliferation of spin-off and related fields (see the topic list, below), while maintaining a core emphasis befitting its name. It has also succeeded in enforcing an emphasis on quality.
Book Synopsis Special issue neural networks and operations research by :
Download or read book Special issue neural networks and operations research written by and published by . This book was released on 1992 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Neural Network Learning and Expert Systems by : Stephen I. Gallant
Download or read book Neural Network Learning and Expert Systems written by Stephen I. Gallant and published by MIT Press. This book was released on 1993 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: presents a unified and in-depth development of neural network learning algorithms and neural network expert systems
Book Synopsis Special issue: Neural networks in remote sensing by : Peter M. Atkinson
Download or read book Special issue: Neural networks in remote sensing written by Peter M. Atkinson and published by . This book was released on 1997 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Efficient Processing of Deep Neural Networks by : Vivienne Sze
Download or read book Efficient Processing of Deep Neural Networks written by Vivienne Sze and published by Springer Nature. This book was released on 2022-05-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.
Book Synopsis Person Re-Identification by : Shaogang Gong
Download or read book Person Re-Identification written by Shaogang Gong and published by Springer Science & Business Media. This book was released on 2014-01-03 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book of its kind dedicated to the challenge of person re-identification, this text provides an in-depth, multidisciplinary discussion of recent developments and state-of-the-art methods. Features: introduces examples of robust feature representations, reviews salient feature weighting and selection mechanisms and examines the benefits of semantic attributes; describes how to segregate meaningful body parts from background clutter; examines the use of 3D depth images and contextual constraints derived from the visual appearance of a group; reviews approaches to feature transfer function and distance metric learning and discusses potential solutions to issues of data scalability and identity inference; investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference and describes techniques for improving post-rank search efficiency; explores the design rationale and implementation considerations of building a practical re-identification system.
Book Synopsis Special issue on neural networks by :
Download or read book Special issue on neural networks written by and published by . This book was released on 1994 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Special Issue on Complex Valued Neural Networks by : Garimella Rama Murthy
Download or read book Special Issue on Complex Valued Neural Networks written by Garimella Rama Murthy and published by . This book was released on 2008 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spiking Neural Networks written by and published by . This book was released on 2014 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence in the Age of Neural Networks and Brain Computing by : Robert Kozma
Download or read book Artificial Intelligence in the Age of Neural Networks and Brain Computing written by Robert Kozma and published by Academic Press. This book was released on 2018-10-30 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity and smart autonomous search engines. The book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. The success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel and Amazon can be interpreted using this book. Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN) Authored by top experts, global field pioneers and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making Edited by high-level academics and researchers in intelligent systems and neural networks
