Advanced Neural Computers

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Advanced Neural Computers

R. Eckmiller
Advanced Neural Computers Book PDF

Author : R. Eckmiller
Publisher : Elsevier
Page : 464 pages
File Size : 47,8 Mb
Release : 2014-06-28
Category : Computers
ISBN : 9781483294278

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Advanced Neural Computers by R. Eckmiller Pdf

This book is the outcome of the International Symposium on Neural Networks for Sensory and Motor Systems (NSMS) held in March 1990 in the FRG. The NSMS symposium assembled 45 invited experts from Europe, America and Japan representing the fields of Neuroinformatics, Computer Science, Computational Neuroscience, and Neuroscience. As a rapidly-published report on the state of the art in Neural Computing it forms a reference book for future research in this highly interdisciplinary field and should prove useful in the endeavor to transfer concepts of brain function and structure to novel neural computers with adaptive, dynamical neural net topologies. A feature of the book is the completeness of the references provided. An alphabetical list of all references quoted in the papers is given, as well as a separate list of general references to help newcomers to the field. A subject index and author index also facilitate access to various details.

Neural Computers

Rolf Eckmiller,Christoph v.d. Malsburg
Neural Computers Book PDF

Author : Rolf Eckmiller,Christoph v.d. Malsburg
Publisher : Springer Science & Business Media
Page : 562 pages
File Size : 55,9 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642837401

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Neural Computers by Rolf Eckmiller,Christoph v.d. Malsburg Pdf

the outcome of a NATO Advanced Research Workshop (ARW) This book is held in Neuss (near Dusseldorf), Federal Republic of Germany from 28 September to 2 October, 1987. The workshop assembled some 50 invited experts from Europe, Ameri ca, and Japan representing the fields of Neuroscience, Computational Neuroscience, Cellular Automata, Artificial Intelligence, and Compu ter Design; more than 20 additional scientists from various countries attended as observers. The 50 contributions in this book cover a wide range of topics, including: Neural Network Architecture, Learning and Memory, Fault Tolerance, Pattern Recognition, and Motor Control in Brains versus Neural Computers. Twelve of these contributions are review papers. The readability of this book was enhanced by a number of measures: * The contributions are arranged in seven chapters. * A separate List of General References helps newcomers to this ra pidly growing field to find introductory books. * The Collection of References from all Contributions provides an alphabetical list of all references quoted in the individual con tributions. * Separate Reference Author and Subject Indices facilitate access to various details. Group Reports (following the seven chapters) summarize the discus sions regarding four specific topics relevant for the 'state of the art' in Neural Computers.

Advanced Methods in Neural Computing

Philip D. Wasserman
Advanced Methods in Neural Computing Book PDF

Author : Philip D. Wasserman
Publisher : Van Nostrand Reinhold Company
Page : 280 pages
File Size : 42,7 Mb
Release : 1993
Category : Computers
ISBN : UOM:39015029904201

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Advanced Methods in Neural Computing by Philip D. Wasserman Pdf

This is the engineer's guide to artificial neural networks, the advanced computing innovation which is posed to sweep into the world of business and industry. The author presents the basic principles and advanced concepts by means of high-performance paradigms which function effectively in real-world situations.

Deep Learning for Computer Vision

Rajalingappaa Shanmugamani
Deep Learning for Computer Vision Book PDF

Author : Rajalingappaa Shanmugamani
Publisher : Packt Publishing Ltd
Page : 304 pages
File Size : 44,9 Mb
Release : 2018-01-23
Category : Computers
ISBN : 9781788293358

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Deep Learning for Computer Vision by Rajalingappaa Shanmugamani Pdf

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks Key Features Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more Includes tips on optimizing and improving the performance of your models under various constraints Book Description Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. What you will learn Set up an environment for deep learning with Python, TensorFlow, and Keras Define and train a model for image and video classification Use features from a pre-trained Convolutional Neural Network model for image retrieval Understand and implement object detection using the real-world Pedestrian Detection scenario Learn about various problems in image captioning and how to overcome them by training images and text together Implement similarity matching and train a model for face recognition Understand the concept of generative models and use them for image generation Deploy your deep learning models and optimize them for high performance Who this book is for This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python—and some understanding of machine learning concepts—is required to get the best out of this book.

Neural Computing for Advanced Applications

Haijun Zhang,Zhao Zhang,Zhou Wu,Tianyong Hao
Neural Computing for Advanced Applications Book PDF

Author : Haijun Zhang,Zhao Zhang,Zhou Wu,Tianyong Hao
Publisher : Springer Nature
Page : 542 pages
File Size : 46,9 Mb
Release : 2020-08-12
Category : Computers
ISBN : 9789811576706

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Neural Computing for Advanced Applications by Haijun Zhang,Zhao Zhang,Zhou Wu,Tianyong Hao Pdf

This book presents refereed proceedings of the First International Conference on Neural Computing for Advanced Applications, NCAA 2020, held in July, 2020. Due to the COVID-19 pandemic the conference was held online. The 36 full papers and 7 short papers were thorougly reviewed and selected from a total of 113 qualified submissions. The papers present resent research on such topics as neural network theory, and cognitive sciences, machine learning, data mining, data security & privacy protection, and data-driven applications, computational intelligence, nature-inspired optimizers, and their engineering applications, cloud/edge/fog computing, the Internet of Things/Vehicles (IoT/IoV), and their system optimization, control systems, network synchronization, system integration, and industrial artificial intelligence, fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences, computer vision, image processing, and their industrial applications, and natural language processing, machine translation, knowledge graphs, and their applications.

Advanced Methods and Deep Learning in Computer Vision

E. R. Davies,Matthew Turk
Advanced Methods and Deep Learning in Computer Vision Book PDF

Author : E. R. Davies,Matthew Turk
Publisher : Academic Press
Page : 584 pages
File Size : 52,8 Mb
Release : 2021-11-09
Category : Computers
ISBN : 9780128221495

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Advanced Methods and Deep Learning in Computer Vision by E. R. Davies,Matthew Turk Pdf

Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students. Provides an important reference on deep learning and advanced computer methods that was created by leaders in the field Illustrates principles with modern, real-world applications Suitable for self-learning or as a text for graduate courses

Neural Computing for Advanced Applications

Haijun Zhang,Zhi Yang,Zhao Zhang,Zhou Wu,Tianyong Hao
Neural Computing for Advanced Applications Book PDF

Author : Haijun Zhang,Zhi Yang,Zhao Zhang,Zhou Wu,Tianyong Hao
Publisher : Springer Nature
Page : 774 pages
File Size : 53,5 Mb
Release : 2021-08-20
Category : Computers
ISBN : 9789811651885

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Neural Computing for Advanced Applications by Haijun Zhang,Zhi Yang,Zhao Zhang,Zhou Wu,Tianyong Hao Pdf

This book presents refereed proceedings of the Second International Conference Neural Computing for Advanced Applications, NCAA 2021, held in Guangzhou, China, in August, 2021. The 54 full papers papers were thorougly reviewed and selected from a total of 144 qualified submissions. The papers are organized in topical sections on neural network theory, cognitive sciences, neuro-system hardware implementations, and NN-based engineering applications; machine learning, data mining, data security and privacy protection, and data-driven applications; neural computing-based fault diagnosis, fault forecasting, prognostic management, and system modeling; computational intelligence, nature-inspired optimizers, and their engineering applications; fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences; control systems, network synchronization, system integration, and industrial artificial intelligence; computer vision, image processing, and their industrial applications; cloud/edge/fog computing, the Internet of Things/Vehicles(IoT/IoV), and their system optimization; spreading dynamics, forecasting, and other intelligent techniques against coronavirus disease (COVID-19).

Guide to Neural Computing Applications

Lionel Tarassenko
Guide to Neural Computing Applications Book PDF

Author : Lionel Tarassenko
Publisher : Elsevier
Page : 160 pages
File Size : 44,9 Mb
Release : 1998-01-30
Category : Computers
ISBN : 9780080512600

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Guide to Neural Computing Applications by Lionel Tarassenko Pdf

Neural networks have shown enormous potential for commercial exploitation over the last few years but it is easy to overestimate their capabilities. A few simple algorithms will learn relationships between cause and effect or organise large volumes of data into orderly and informative patterns but they cannot solve every problem and consequently their application must be chosen carefully and appropriately. This book outlines how best to make use of neural networks. It enables newcomers to the technology to construct robust and meaningful non-linear models and classifiers and benefits the more experienced practitioner who, through over familiarity, might otherwise be inclined to jump to unwarranted conclusions. The book is an invaluable resource not only for those in industry who are interested in neural computing solutions, but also for final year undergraduates or graduate students who are working on neural computing projects. It provides advice which will help make the best use of the growing number of commercial and public domain neural network software products, freeing the specialist from dependence upon external consultants.

International Conference on Neural Computing for Advanced Applications

Haijun Zhang,Yinggen Ke,Zhou Wu,Tianyong Hao,Zhao Zhang,Weizhi Meng,Yuanyuan Mu
International Conference on Neural Computing for Advanced Applications Book PDF

Author : Haijun Zhang,Yinggen Ke,Zhou Wu,Tianyong Hao,Zhao Zhang,Weizhi Meng,Yuanyuan Mu
Publisher : Springer Nature
Page : 627 pages
File Size : 46,8 Mb
Release : 2023-08-29
Category : Computers
ISBN : 9789819958474

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International Conference on Neural Computing for Advanced Applications by Haijun Zhang,Yinggen Ke,Zhou Wu,Tianyong Hao,Zhao Zhang,Weizhi Meng,Yuanyuan Mu Pdf

The two-volume set CCIS 1869 and 1870 constitutes the refereed proceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023, held in Hefei, China, in July 2023. The 83 full papers and 1 short paper presented in these proceedings were carefully reviewed and selected from 211 submissions. The papers have been organized in the following topical sections: Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications; Machine learning and deep learning for data mining and data-driven applications; Computational intelligence, nature-inspired optimizers, and their engineering applications; Deep learning-driven pattern recognition, computer vision and its industrial applications; Natural language processing, knowledge graphs, recommender systems, and their applications; Neural computing-based fault diagnosis and forecasting, prognostic management, and cyber-physical system security; Sequence learning for spreading dynamics, forecasting, and intelligent techniques against epidemic spreading (2); Applications of Data Mining, Machine Learning and Neural Computing in Language Studies; Computational intelligent Fault Diagnosis and Fault-Tolerant Control, and Their Engineering Applications; and Other Neural computing-related topics.

Artificial Neural Networks: Advanced Principles

Jeremy Rogerson
Artificial Neural Networks Advanced Principles Book PDF

Author : Jeremy Rogerson
Publisher : Unknown
Page : 192 pages
File Size : 42,8 Mb
Release : 2019-06-27
Category : Electronic
ISBN : 1682856690

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Artificial Neural Networks: Advanced Principles by Jeremy Rogerson Pdf

Artificial neural networks refer to the computing systems inspired by biological neural networks. They are based on nodes or artificial neurons, which are a replica of biological neurons found in the brain of animals. This enables them to learn and thereby perform tasks by considering examples. The use of artificial neural networks is vast as they are applied in varied fields like medical diagnosis, speech recognition, computer vision, machine translation, etc. Some common variants include convolutional neural networks, deep stacking networks, deep belief networks, deep predictive coding networks, etc. The theoretical properties of artificial neural networks are capacity, generalization and statistics, computational power, convergence, etc. This book is a valuable compilation of topics, ranging from the basic to the most complex advancements in the field of artificial neural networks. The book attempts to assist those with a goal of delving into this field. The various studies that are constantly contributing towards advancing technologies and evolution of this field are examined in detail.

International Conference on Neural Computing for Advanced Applications

Haijun Zhang,Yinggen Ke,Zhou Wu,Tianyong Hao,Zhao Zhang,Weizhi Meng,Yuanyuan Mu
International Conference on Neural Computing for Advanced Applications Book PDF

Author : Haijun Zhang,Yinggen Ke,Zhou Wu,Tianyong Hao,Zhao Zhang,Weizhi Meng,Yuanyuan Mu
Publisher : Springer Nature
Page : 595 pages
File Size : 51,7 Mb
Release : 2023-08-30
Category : Computers
ISBN : 9789819958443

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International Conference on Neural Computing for Advanced Applications by Haijun Zhang,Yinggen Ke,Zhou Wu,Tianyong Hao,Zhao Zhang,Weizhi Meng,Yuanyuan Mu Pdf

The two-volume set CCIS 1869 and 1870 constitutes the refereed proceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023, held in Hefei, China, in July 2023. The 83 full papers and 1 short paper presented in these proceedings were carefully reviewed and selected from 211 submissions. The papers have been organized in the following topical sections: Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications; Machine learning and deep learning for data mining and data-driven applications; Computational intelligence, nature-inspired optimizers, and their engineering applications; Deep learning-driven pattern recognition, computer vision and its industrial applications; Natural language processing, knowledge graphs, recommender systems, and their applications; Neural computing-based fault diagnosis and forecasting, prognostic management, and cyber-physical system security; Sequence learning for spreading dynamics, forecasting, and intelligent techniques against epidemic spreading (2); Applications of Data Mining, Machine Learning and Neural Computing in Language Studies; Computational intelligent Fault Diagnosis and Fault-Tolerant Control, and Their Engineering Applications; and Other Neural computing-related topics.

ADVANCED TOPICS IN NEURAL NETWORKS WITH MATLAB. PARALLEL COMPUTING, OPTIMIZE AND TRAINING

PEREZ C.
ADVANCED TOPICS IN NEURAL NETWORKS WITH MATLAB PARALLEL COMPUTING OPTIMIZE AND TRAINING Book PDF

Author : PEREZ C.
Publisher : CESAR PEREZ
Page : 78 pages
File Size : 43,8 Mb
Release : 2023-12-13
Category : Computers
ISBN : 9781974082049

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ADVANCED TOPICS IN NEURAL NETWORKS WITH MATLAB. PARALLEL COMPUTING, OPTIMIZE AND TRAINING by PEREZ C. Pdf

Neural networks are inherently parallel algorithms. Multicore CPUs, graphical processing units (GPUs), and clusters of computers with multiple CPUs and GPUs can take advantage of this parallelism. Parallel Computing Toolbox, when used in conjunction with Neural Network Toolbox, enables neural network training and simulation to take advantage of each mode of parallelism. Parallel Computing Toolbox allows neural network training and simulation to run across multiple CPU cores on a single PC, or across multiple CPUs on multiple computers on a network using MATLAB Distributed Computing Server. Using multiple cores can speed calculations. Using multiple computers can allow you to solve problems using data sets too big to fit in the RAM of a single computer. The only limit to problem size is the total quantity of RAM available across all computers. Distributed and GPU computing can be combined to run calculations across multiple CPUs and/or GPUs on a single computer, or on a cluster with MATLAB Distributed Computing Server. It is desirable to determine the optimal regularization parameters in an automated fashion. One approach to this process is the Bayesian framework. In this framework, the weights and biases of the network are assumed to be random variables with specified distributions. The regularization parameters are related to the unknown variances associated with these distributions. You can then estimate these parameters using statistical techniques. It is very difficult to know which training algorithm will be the fastest for a given problem. It depends on many factors, including the complexity of the problem, the number of data points in the training set, the number of weights and biases in the network, the error goal, and whether the network is being used for pattern recognition (discriminant analysis) or function approximation (regression). This book compares the various training algorithms. One of the problems that occur during neural network training is called overfitting. The error on the training set is driven to a very small value, but when new data is presented to the network the error is large. The network has memorized the training examples, but it has not learned to generalize to new situations. This book develops the following topics: Neural Networks with Parallel and GPU Computing Deep Learning Optimize Neural Network Training Speed and Memory Improve Neural Network Generalization and Avoid Overfitting Create and Train Custom Neural Network Architectures Deploy Training of Neural Networks Perceptron Neural Networks Linear Neural Networks Hopfield Neural Network Neural Network Object Reference Neural Network Simulink Block Library Deploy Neural Network Simulink Diagrams

Neural Computing for Advanced Applications

Haijun Zhang,Yuehui Chen,Xianghua Chu,Zhao Zhang,Tianyong Hao,Zhou Wu,Yimin Yang
Neural Computing for Advanced Applications Book PDF

Author : Haijun Zhang,Yuehui Chen,Xianghua Chu,Zhao Zhang,Tianyong Hao,Zhou Wu,Yimin Yang
Publisher : Springer Nature
Page : 566 pages
File Size : 53,6 Mb
Release : 2022-10-20
Category : Computers
ISBN : 9789811961427

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Neural Computing for Advanced Applications by Haijun Zhang,Yuehui Chen,Xianghua Chu,Zhao Zhang,Tianyong Hao,Zhou Wu,Yimin Yang Pdf

The two-volume Proceedings set CCIS 1637 and 1638 constitutes the refereed proceedings of the Third International Conference on Neural Computing for Advanced Applications, NCAA 2022, held in Jinan, China, during July 8–10, 2022. The 77 papers included in these proceedings were carefully reviewed and selected from 205 submissions. These papers were categorized into 10 technical tracks, i.e., neural network theory, and cognitive sciences, machine learning, data mining, data security & privacy protection, and data-driven applications, computational intelligence, nature-inspired optimizers, and their engineering applications, cloud/edge/fog computing, the Internet of Things/Vehicles (IoT/IoV), and their system optimization, control systems, network synchronization, system integration, and industrial artificial intelligence, fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences, computer vision, image processing, and their industrial applications, natural language processing, machine translation, knowledge graphs, and their applications, Neural computing-based fault diagnosis, fault forecasting, prognostic management, and system modeling, and Spreading dynamics, forecasting, and other intelligent techniques against coronavirus disease (COVID-19).

Static and Dynamic Neural Networks

Madan Gupta,Liang Jin,Noriyasu Homma
Static and Dynamic Neural Networks Book PDF

Author : Madan Gupta,Liang Jin,Noriyasu Homma
Publisher : John Wiley & Sons
Page : 752 pages
File Size : 52,8 Mb
Release : 2004-04-05
Category : Computers
ISBN : 9780471460923

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Static and Dynamic Neural Networks by Madan Gupta,Liang Jin,Noriyasu Homma Pdf

Neuronale Netze haben sich in vielen Bereichen der Informatik und künstlichen Intelligenz, der Robotik, Prozeßsteuerung und Entscheidungsfindung bewährt. Um solche Netze für immer komplexere Aufgaben entwickeln zu können, benötigen Sie solide Kenntnisse der Theorie statischer und dynamischer neuronaler Netze. Aneignen können Sie sie sich mit diesem Lehrbuch! Alle theoretischen Konzepte sind in anschaulicher Weise mit praktischen Anwendungen verknüpft. Am Ende jedes Kapitels können Sie Ihren Wissensstand anhand von Übungsaufgaben überprüfen.

Neural Computing for Advanced Applications

Haijun Zhang,Yuehui Chen,Xianghua Chu,Zhao Zhang,Tianyong Hao,Zhou Wu,Yimin Yang
Neural Computing for Advanced Applications Book PDF

Author : Haijun Zhang,Yuehui Chen,Xianghua Chu,Zhao Zhang,Tianyong Hao,Zhou Wu,Yimin Yang
Publisher : Springer Nature
Page : 532 pages
File Size : 45,6 Mb
Release : 2022-10-20
Category : Computers
ISBN : 9789811961359

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Neural Computing for Advanced Applications by Haijun Zhang,Yuehui Chen,Xianghua Chu,Zhao Zhang,Tianyong Hao,Zhou Wu,Yimin Yang Pdf

The two-volume Proceedings set CCIS 1637 and 1638 constitutes the refereed proceedings of the Third International Conference on Neural Computing for Advanced Applications, NCAA 2022, held in Jinan, China, during July 8–10, 2022. The 77 papers included in these proceedings were carefully reviewed and selected from 205 submissions. These papers were categorized into 10 technical tracks, i.e., neural network theory, and cognitive sciences, machine learning, data mining, data security & privacy protection, and data-driven applications, computational intelligence, nature-inspired optimizers, and their engineering applications, cloud/edge/fog computing, the Internet of Things/Vehicles (IoT/IoV), and their system optimization, control systems, network synchronization, system integration, and industrial artificial intelligence, fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences, computer vision, image processing, and their industrial applications, natural language processing, machine translation, knowledge graphs, and their applications, Neural computing-based fault diagnosis, fault forecasting, prognostic management, and system modeling, and Spreading dynamics, forecasting, and other intelligent techniques against coronavirus disease (COVID-19).