Advances In Pattern Recognition Systems Using Neural Network Technologies
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Advances In Pattern Recognition Systems Using Neural Network Technologies
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Author : Patrick S P Wang
language : en
Publisher: World Scientific
Release Date : 1994-01-01
Advances In Pattern Recognition Systems Using Neural Network Technologies written by Patrick S P Wang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-01-01 with categories.
Contents:A Connectionist Approach to Speech Recognition (Y Bengio)Signature Verification Using a “Siamese” Time Delay Neural Network (J Bromley et al.)Boosting Performance in Neural Networks (H Drucker et al.)An Integrated Architecture for Recognition of Totally Unconstrained Handwritten Numerals (A Gupta et al.)Time-Warping Network: A Neural Approach to Hidden Markov Model Based Speech Recognition (E Levin et al.)Computing Optical Flow with a Recurrent Neural Network (H Li & J Wang)Integrated Segmentation and Recognition through Exhaustive Scans or Learned Saccadic Jumps (G L Martin et al.)Experimental Comparison of the Effect of Order in Recurrent Neural Networks (C B Miller & C L Giles)Adaptive Classification by Neural Net Based Prototype Populations (K Peleg & U Ben-Hanan)A Neural System for the Recognition of Partially Occluded Objects in Cluttered Scenes: A Pilot Study (L Wiskott & C von der Malsburg)and other papers Readership: Computer scientists and engineers.
Advances In Pattern Recognition Research
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Author : Thomas Lu
language : en
Publisher:
Release Date : 2018
Advances In Pattern Recognition Research written by Thomas Lu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Computers categories.
Artificial Intelligence (AI) has become a popular research topic recently. Pattern recognition (PR) is an important part of an AI system. If the AI is considered as the digital "brain", then the PR is the visual and auditory "cortex" that converts the optical signals from the eyes and the acoustic signals from the ears to meaningful symbolic texts that the brain can digest. Over the past 40+ years, the processing speed of a digital computer has increased from kbits/s to tera floating point operations per second (TFLOPS), a 109 times acceleration. PR research has made significant advancements along the advancement of digital hardware, especially the graphical processing unit (GPU) technology that helps the rapid processing of complex images. In this book, the authors have collected the latest work from leading researchers in the PR fields. The topics are broad, which include optical implementation of various filters, digital implementation of state-of-the-art neural network (NN) training methods, and the latest deep leaning (DL) models. We also included applications of PR in various fields.In Chapter One, an optical implementation of an advanced multi-stage automatic target recognition (ATR) processor is introduced. The grayscale optical correlator (GOC) has been implemented in a compact and rugged 2x2x2 inch3 cube. It is the world's smallest optical correlator. Combined with a neural network (NN) classifier, the system becomes an efficient embedded vision system that learns to detect multiple targets embedded in large images with unknown backgrounds.The deep neural network (DNN) learning model has become a phenomenal research topic. In Chapter Two, state-of-the-art DNN architectures are introduced. Applications of DNN in object segmentation, recognition and augmented reality are presented.In Chapter Three, recent trends on invariant pattern recognition via joint transform correlation (JTC) are presented. Enhanced correlation filters such as logarithmic fringe-adjusted filter (LFAF), phase-encoded fringe-adjusted JTC (PJTC), shifted PJTC (SPJTC), Gaussian filtering based SPJTC (G-SPJTC) and Gaussian filter based logarithmic fringe-adjusted JTC (G-LFJTC) are discussed and tested for face recognition and texture identification.In Chapter Four, a class of optical synthetic filters, the optimal trade-off maximum average correlation height (OT-MACH) filter is investigated. The spatial domain OT-MACH (SPOT-MACH) filters are compared to the frequency domain filters for PR in infrared (IR) images with poor contrast or large illumination gradients.Cyber security has become an important research topic. Most cyber-attacks follow a certain pattern. Chapter Five discusses the applications of DL models as a PR technique to exploit this underlying characteristic of the cyber-attack data in information security.Chapter Six discusses the recognition of handwritten numerals in the Modified National Institute of Standard (MNIST) database using probabilistic neural network (PNN) models.Chapter Seven discusses several training methodologies of the artificial neural network (ANN) models. In Chapter Eight, the ANN training models are used in extracting spatial features for printed characters recognition.
Advances In Pattern Recognition And Artificial Intelligence
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Author : Marleah Blom
language : en
Publisher: World Scientific
Release Date : 2021-11-16
Advances In Pattern Recognition And Artificial Intelligence written by Marleah Blom and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-16 with Computers categories.
This book includes reviewed papers by international scholars from the 2020 International Conference on Pattern Recognition and Artificial Intelligence (held online). The papers have been expanded to provide more details specifically for the book. It is geared to promote ongoing interest and understanding about pattern recognition and artificial intelligence. Like the previous book in the series, this book covers a range of topics and illustrates potential areas where pattern recognition and artificial intelligence can be applied. It highlights, for example, how pattern recognition and artificial intelligence can be used to classify, predict, detect and help promote further discoveries related to credit scores, criminal news, national elections, license plates, gender, personality characteristics, health, and more.Chapters include works centred on medical and financial applications as well as topics related to handwriting analysis and text processing, internet security, image analysis, database creation, neural networks and deep learning. While the book is geared to promote interest from the general public, it may also be of interest to graduate students and researchers in the field.
Cross Disciplinary Applications Of Artificial Intelligence And Pattern Recognition Advancing Technologies
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Author : Mago, Vijay Kumar
language : en
Publisher: IGI Global
Release Date : 2011-12-31
Cross Disciplinary Applications Of Artificial Intelligence And Pattern Recognition Advancing Technologies written by Mago, Vijay Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-31 with Computers categories.
The need for intelligent machines in areas such as medical diagnostics, biometric security systems, and image processing motivates researchers to develop and explore new techniques, algorithms, and applications in this evolving field.Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies provides a common platform for researchers to present theoretical and applied research findings for enhancing and developing intelligent systems. Through its discussions of advances in and applications of pattern recognition technologies and artificial intelligence, this reference highlights core concepts in biometric imagery, feature recognition, and other related fields, along with their applicability.
Progress In Pattern Recognition
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Author : Sameer Singh
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-03
Progress In Pattern Recognition written by Sameer Singh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-03 with Computers categories.
This book features a collection of articles presented at the 2007 Workshop on Advances in Pattern Recognition, which was organized in conjunction with the 5th International Summer School on Pattern Recognition. It provides readers with the state-of-the-art algorithms in the area of pattern recognition as well as a presentation of the cutting edge applications within the field.
Pattern Recognition With Neural Networks In C
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Author : Abhijit S. Pandya
language : en
Publisher: CRC Press
Release Date : 2020-10-12
Pattern Recognition With Neural Networks In C written by Abhijit S. Pandya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-12 with Computers categories.
The addition of artificial neural network computing to traditional pattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical guide to the application of artificial neural networks. Geared toward the practitioner, Pattern Recognition with Neural Networks in C++ covers pattern classification and neural network approaches within the same framework. Through the book's presentation of underlying theory and numerous practical examples, readers gain an understanding that will allow them to make judicious design choices rendering neural application predictable and effective. The book provides an intuitive explanation of each method for each network paradigm. This discussion is supported by a rigorous mathematical approach where necessary. C++ has emerged as a rich and descriptive means by which concepts, models, or algorithms can be precisely described. For many of the neural network models discussed, C++ programs are presented for the actual implementation. Pictorial diagrams and in-depth discussions explain each topic. Necessary derivative steps for the mathematical models are included so that readers can incorporate new ideas into their programs as the field advances with new developments. For each approach, the authors clearly state the known theoretical results, the known tendencies of the approach, and their recommendations for getting the best results from the method. The material covered in the book is accessible to working engineers with little or no explicit background in neural networks. However, the material is presented in sufficient depth so that those with prior knowledge will find this book beneficial. Pattern Recognition with Neural Networks in C++ is also suitable for courses in neural networks at an advanced undergraduate or graduate level. This book is valuable for academic as well as practical research.
Advances In Neural Networks Computational And Theoretical Issues
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Author : Simone Bassis
language : en
Publisher: Springer
Release Date : 2015-06-05
Advances In Neural Networks Computational And Theoretical Issues written by Simone Bassis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-05 with Technology & Engineering categories.
This book collects research works that exploit neural networks and machine learning techniques from a multidisciplinary perspective. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and bio-inspired memristor-based networks. Providing insights into the latest research interest from a pool of international experts coming from different research fields, the volume becomes valuable to all those with any interest in a holistic approach to implement believable, autonomous, adaptive and context-aware Information Communication Technologies.
Soft Computing Approach To Pattern Recognition And Image Processing
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Author : Ashish Ghosh
language : en
Publisher: World Scientific
Release Date : 2002
Soft Computing Approach To Pattern Recognition And Image Processing written by Ashish Ghosh and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
This volume provides a collection of sixteen articles containing review and new material. In a unified way, they describe the recent development of theories and methodologies in pattern recognition, image processing and vision using fuzzy logic, artificial neural networks, genetic algorithms, rough sets and wavelets with significant real life applications. The book details the theory of granular computing and the role of a rough-neuro approach as a way of computing with words and designing intelligent recognition systems. It also demonstrates applications of the soft computing paradigm to case based reasoning, data mining and bio-informatics with a scope for future research. The contributors from around the world present a balanced mixture of current theory, algorithms and applications, making the book an extremely useful resource for students and researchers alike. Contents: Pattern Recognition: Multiple Classifier Systems; Building Decision Trees from the Fourier Spectrum of a Tree Ensemble; Clustering Large Data Sets; Multi-objective Variable String Genetic Classifier: Application to Remote Sensing Imagery; Image Processing and Vision: Dissimilarity Measures Between Fuzzy Sets or Fuzzy Structures; Early Vision: Concepts and Algorithms; Self-organizing Neural Network for Multi-level Image Segmentation; Geometric Transformation by Moment Method with Wavelet Matrix; New Computationally Efficient Algorithms for Video Coding; Soft Computing for Computational Media Aesthetics: Analyzing Video Content for Meaning; Granular Computing and Case Based Reasoning: Towards Granular Multi-agent Systems; Granular Computing and Pattern Recognition; Case Base Maintenance: A Soft Computing Perspective; Real Life Applications: Autoassociative Neural Network Models for Pattern Recognition Tasks in Speech and Image; Protein Structure Prediction Using Soft Computing; Pattern Classification for Biological Data Mining. Readership: Upper level undergraduates, graduates, researchers, academics and industrialists.
Advances In Neural Networks Isnn 2009
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Author : Wen Yu
language : en
Publisher: Springer
Release Date : 2009-05-21
Advances In Neural Networks Isnn 2009 written by Wen Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-21 with Computers categories.
This book and its companion volumes, LNCS vols. 5551, 5552 and 5553, constitute the proceedings of the 6th International Symposium on Neural Networks (ISNN 2009), held during May 26–29, 2009 in Wuhan, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural n- works and related fields, with a successful sequence of ISNN symposia held in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), and Beijing (2008). Following the tradition of the ISNN series, ISNN 2009 provided a high-level inter- tional forum for scientists, engineers, and educators to present state-of-the-art research in neural networks and related fields, and also to discuss with international colleagues on the major opportunities and challenges for future neural network research. Over the past decades, the neural network community has witnessed tremendous - forts and developments in all aspects of neural network research, including theoretical foundations, architectures and network organizations, modeling and simulation, - pirical study, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, have provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large-scale, and n- worked brain-like intelligent systems. This long-term goal can only be achieved with the continuous efforts of the community to seriously investigate different issues of the neural networks and related fields.
Neural Networks For Pattern Recognition
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Author : Christopher M. Bishop
language : en
Publisher: Oxford University Press
Release Date : 1995-11-23
Neural Networks For Pattern Recognition written by Christopher M. Bishop and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-11-23 with Computers categories.
Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.