Advances In Pattern Recognition And Artificial Intelligence

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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

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Author : V. K. Mago
language : en
Publisher:
Release Date : 2012

Cross Disciplinary Applications Of Artificial Intelligence And Pattern Recognition written by V. K. Mago and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Artificial intelligence categories.

"This book provides a common platform for researchers to present theoretical and applied research findings for enhancing and developing intelligent systems, discussing advances in and applications of pattern recognition technologies and artificial intelligence"--

Pattern Recognition And Artificial Intelligence

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Author : Mass.) Joint Workshop on Pattern Recognition and Artificial Intelligence (1976 : Hyannis
language : en
Publisher:
Release Date : 1976

Pattern Recognition And Artificial Intelligence written by Mass.) Joint Workshop on Pattern Recognition and Artificial Intelligence (1976 : Hyannis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with categories.

Machine Learning In Image Analysis And Pattern Recognition

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Author : Munish Kumar
language : en
Publisher:
Release Date : 2021

Machine Learning In Image Analysis And Pattern Recognition written by Munish Kumar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.

This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.

Recent Advances In Artificial Intelligence And Data Engineering

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Author : Pushparaj Shetty D.
language : en
Publisher: Springer Nature
Release Date : 2021-10-31

Recent Advances In Artificial Intelligence And Data Engineering written by Pushparaj Shetty D. and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-31 with Computers categories.

This book presents select proceedings of the International Conference on Artificial Intelligence and Data Engineering (AIDE 2020). Various topics covered in this book include deep learning, neural networks, machine learning, computational intelligence, cognitive computing, fuzzy logic, expert systems, brain-machine interfaces, ant colony optimization, natural language processing, bioinformatics and computational biology, cloud computing, machine vision and robotics, ambient intelligence, intelligent transportation, sensing and sensor networks, big data challenge, data science, high performance computing, data mining and knowledge discovery, and data privacy and security. The book will be a valuable reference for beginners, researchers, and professionals interested in artificial intelligence, robotics and data engineering.

Pattern Recognition And Machine Learning

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Author : Christopher M. Bishop
language : en
Publisher: Springer Verlag
Release Date : 2006-08-17

Pattern Recognition And Machine Learning written by Christopher M. Bishop and has been published by Springer Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-17 with Computers categories.

This is the first text on pattern recognition to present the Bayesian viewpoint, one that has become increasing popular in the last five years. It presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It provides the first text to use graphical models to describe probability distributions when there are no other books that apply graphical models to machine learning. It is also the first four-color book on pattern recognition. The book is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. Extensive support is provided for course instructors, including more than 400 exercises, graded according to difficulty. Example solutions for a subset of the exercises are available from the book web site, while solutions for the remainder can be obtained by instructors from the publisher.

Pattern Recognition And Classification In Time Series Data

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Author : Volna, Eva
language : en
Publisher: IGI Global
Release Date : 2016-07-22

Pattern Recognition And Classification In Time Series Data written by Volna, Eva and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-22 with Computers categories.

Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.

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 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.

Advancements In Artificial Intelligence And Machine Learning

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Author : Asif Khan, Mohammad Kamrul Hasan, Naushad Varish, Mohammed Aslam Husain
language : en
Publisher: Bentham Science Publishers
Release Date : 2025-06-19

Advancements In Artificial Intelligence And Machine Learning written by Asif Khan, Mohammad Kamrul Hasan, Naushad Varish, Mohammed Aslam Husain and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-19 with Computers categories.

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing industries, reshaping the way we interact with technology, and driving innovation across multiple disciplines. Advancements in Artificial Intelligence and Machine Learning is a comprehensive exploration of the latest developments, applications, and challenges in AI and ML, offering insights into cutting-edge research and real-world implementations. This book is a collection of twelve chapters, each exploring a distinct application of Artificial Intelligence (AI) and Machine Learning (ML). It begins with an overview of AI’s transformative role in Next-Gen Mechatronics, followed by a comprehensive review of key advancements and trends in the field. The book then examines AI’s impact across diverse sectors, including energy, digital communication, and security, with topics such as AI-based aging analysis of power transformer oil, AI in social media management, and AI-driven human detection systems. Further chapters address sentiment analysis, visual analysis for image processing, and the integration of AI in smart grid networks. The volume also covers AI applications in hardware security for wireless sensor networks, drone robotics, and crime prevention systems. The final set of chapters highlight AI’s role in healthcare and automation, including an AI-assisted system for women’s safety in India and the use of EfficientNet B0 CNN architecture for brain tumor detection and classification. Together, these chapters showcase the versatility and growing influence of AI and ML across critical modern industries. Key features A multidisciplinary approach covering AI applications in robotics, cybersecurity, healthcare, and digital transformation in 12 organized chapters. A focus on contemporary challenges and solutions in AI and ML across industries. Research-driven insights from experts and practitioners in the field. Practical discussions on AI-driven automation, security, and intelligent decision-making systems.