|1."Pattern Recognition and Machine Learning (Information Science and Statistics)" by Christopher M Bishop|
“Pattern Recognition and Machine Learning (Information Science and Statistics)” Book Review: This book provides a Bayesian perspective on pattern recognition and describes the use of approximate inference algorithms to obtain quick but approximate solutions in cases where exact solutions are impractical. The book employs graphical models to explain probability distributions and also includes an introduction to basic probability theory, making it an excellent resource for first-time learners. It is particularly useful for postgraduate students studying machine learning in college. Additionally, the book features short-answer questions and multiple-choice questions at the end of each chapter, which allow students to assess their comprehension of the material.
|2."Pattern Recognition: Techniques and Applications" by Rajjan Shinghal|
“Pattern Recognition: Techniques and Applications” Book Review: The procedures for Pattern Recognition are thoroughly covered in this book, which commences by introducing the concept of inductive learning. It encompasses other critical topics, such as feature selection and clustering, and concludes with a chapter that compares the results of classifying a given problem by each procedure, and proposes research on finding their underlying commonality. The end of each chapter features programming and non-programming exercises for readers to test their comprehension. This book is valuable for Engineering students pursuing their undergraduate or master’s degrees in the course on Pattern Recognition. Additionally, practicing engineers in industrial and research organizations can benefit from it as a useful reference.
|3."Markov Models for Pattern Recognition: From Theory to Applications (Advances in Computer Vision and Pattern Recognition)" by Gernot A Fink|
“Markov Models for Pattern Recognition: From Theory to Applications (Advances in Computer Vision and Pattern Recognition)” Book Review: The book serves as a comprehensive manual for Markov models in pattern recognition, encompassing an extensive overview of the EM algorithm. Moreover, it incorporates an assessment of a productive approximate Viterbi-training procedure, a theoretical derivation of perplexity measurement, and a thorough review of multi-pass decoding founded on n-best search. The book places a notable emphasis on practical algorithmic solutions, while providing a depiction of probability quantities and presenting techniques for the setup of hidden Markov models that pertain to particular application domains. This resource is beneficial for pattern recognition practitioners, researchers, and graduate students.
|4."NETLAB: Algorithms for Pattern Recognition (Advances in Computer Vision and Pattern Recognition)" by Ian T Nabney|
“NETLAB: Algorithms for Pattern Recognition (Advances in Computer Vision and Pattern Recognition)” Book Review: The primary focus of this book is to elaborate on neural networks and related data modelling techniques while emphasizing teaching methods that pertain to the practical application of neural networks and pattern analysis issues. The book features demonstrations and examples to illustrate the theory and assist readers in comprehending the algorithms and their practical application. Furthermore, the book teaches the reader how to utilize MATLAB for pattern recognition. This resource is beneficial for both teachers and students of undergraduate and postgraduate courses in pattern recognition. The topics are thoroughly discussed alongside examples to provide a comprehensive understanding of the subject matter.
|5."Pattern Recognition" by Gerhard Rigoll|
“Pattern Recognition” Book Review: Comprising the proceedings of the 30th Symposium of the German Association for Pattern Recognition, this book comprises 53 papers covering various topics. The topics are divided into sections, including learning and classification, tracking, medical image processing, and segmentation. Additionally, the book covers audio, speech, and handwriting recognition, multiview geometry and 3D reconstruction, motion, and matching, as well as image analysis. This resource serves as a valuable learning tool for pattern recognition researchers, students, and teachers, providing technical knowledge based on real-world applications.
|6."Computer Models of Speech Using Fuzzy Algorithms (Advanced Applications in Pattern Recognition)" by Renato de Mori|
“Computer Models of Speech Using Fuzzy Algorithms (Advanced Applications in Pattern Recognition)” Book Review: The subject matter of this book is an in-depth examination of speech recognition, utilizing fuzzy-set theory and artificial intelligence to determine conclusive solutions to the speech-recognition problem. The book presents a research analysis of creating an experimental model capable of comprehending spoken sentences in natural language, delving into the intricacy of the functions carried out by the human brain. The book introduces a method for conceptualizing modules that perform perceptual tasks and combining them in a speech understanding system. This resource is beneficial for computer science and software engineering students and teachers, as well as researchers, owing to its comprehensive research in the field.
|7."A Structural Analysis of Complex Aerial Photographs (Advanced Applications in Pattern Recognition)" by Makoto Nagao and Takashi Matsuyama|
“A Structural Analysis of Complex Aerial Photographs (Advanced Applications in Pattern Recognition)” Book Review: This book offers a profound integration and amalgamation of the two primary approaches to pattern recognition: numerical (or statistical) and structural (linguistic or syntactic). The book’s methodology is based on the natural application of the knowledge-base framework. It systematically and practically achieves structural analysis of complex aerial photographs. The book illustrates the topics with examples and illustrations that provide readers with a practical comprehension of the subject matter. This resource is useful for practitioners working in advanced systems in pattern recognition and will also benefit students, teachers, and researchers interested in the subject.
|8."Computational Intelligence in Multi-Feature Visual Pattern Recognition (Studies in Computational Intelligence)" by Pramod Pisharady and Prahlad Vadakkepat|
“Computational Intelligence in Multi-Feature Visual Pattern Recognition (Studies in Computational Intelligence)” Book Review: This book is a comprehensive collection of computational intelligence algorithms that aim to address the challenges encountered in visual pattern recognition, such as high computational complexity, sensitivity to size and shape, and abundance of pattern features. The first part of the book focuses on research issues in the field and provides a survey of related literature. The second part presents computational intelligence-based algorithms for feature selection and classification, while the third part introduces biologically-inspired algorithms for feature extraction. The material is presented with the help of several figures, charts, tables, and equations that facilitate easy understanding for the reader without the need for instruction. This book will prove to be a valuable resource for teachers, students, and practitioners in the field of pattern recognition.
|9."Video Text Detection (Advances in Computer Vision and Pattern Recognition)" by Tong Lu and Shivakumara Palaiahnakote|
“Video Text Detection (Advances in Computer Vision and Pattern Recognition)” Book Review: This book is designed for the students of computer engineering, researchers and scientists. It delves into the practical applications of video text detection. Its content covers a range of topics, including pattern recognition, document analysis, image processing, and video retrieval. Additionally, the book explores techniques for multi-modal analysis and performance evaluation. By offering in-depth coverage of these subjects, the book serves as a valuable resource for anyone seeking to gain a thorough understanding of video text detection.
|10."Statistical Learning and Pattern Analysis for Image and Video Processing (Advances in Computer Vision and Pattern Recognition)" by Nanning Zheng and Jianru Xue|
“Statistical Learning and Pattern Analysis for Image and Video Processing (Advances in Computer Vision and Pattern Recognition)” Book Review: This book is designed for the students, researchers and scientists. It focuses on several important topics in image processing, including image segmentation, stereo matching, object detection and analysis, and visual tracking. The book also delves into the theoretical underpinnings of these topics, exploring harmonic analysis and partial differential equations. Moreover, the book emphasizes practical applications of video processing and includes examples, exercises, and questions at the end of each chapter.
|11."Pattern Recognition" by Stefan Roth and Arjan Kuijper|
“Pattern Recognition” Book Review: This book covers many topics about pattern recognition, including 3D reconstruction, object recognition, and medical applications. It has 57 solved papers, 37 posters, and lecture notes. This book is a valuable resource for anyone who wants to learn more about pattern recognition.
|12."Image Registration: Principles, Tools and Methods (Advances in Computer Vision and Pattern Recognition)" by A Ardeshir Goshtasby|
“Image Registration: Principles, Tools and Methods (Advances in Computer Vision and Pattern Recognition)” Book Review: This book serves as a comprehensive guide to image registration, introducing its principles, tools, and methods. The book covers the various components of image registration and provides detailed discussions of the analysis tools used for each component, including similarity and dissimilarity measures, point detectors, heterogeneous descriptors, and robust estimators. Other topics explored in the book include image resampling, principle axes, optimization, and model-based methods of transformation. Additionally, an appendix on principal component analysis (PCA) is included, and the book features a range of helpful glossaries. With its in-depth coverage of image registration, this book is an essential resource for anyone working in the field of image analysis.
|13."Automatic Speech Recognition on Mobile Devices and over Communication Networks (Advances in Computer Vision and Pattern Recognition)" by Zheng-Hua Tan|
“Automatic Speech Recognition on Mobile Devices and over Communication Networks (Advances in Computer Vision and Pattern Recognition)” Book Review: This book addresses key issues in the field of computing and networking, providing a collection of papers that explore various aspects of speech recognition, with a particular focus on mobile and over-the-network systems. The book covers automatic speech recognition on mobile devices and over communication networks and begins with a comprehensive introduction to the subject of speech recognition in devices and networks. The book then delves into the study of speech recognition systems, including network, distributed, and embedded speech recognition systems. With its in-depth coverage of speech recognition, the book is an invaluable resource for researchers and engineers working in this rapidly evolving field.
|14."Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications (Advances in Computer Vision and Pattern Recognition)" by imusti|
“Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications (Advances in Computer Vision and Pattern Recognition)” Book Review: This book offers a comprehensive overview of the latest advancements in the application of multimedia interaction and user interfaces for consumer electronics. It delves into topics such as multimedia content analysis and human-machine interaction, as well as introducing novel, computationally efficient algorithms for extracting semantically meaningful audio-visual events. The book also considers the cognitive impacts of modality on human information processing and provides an overview of gesture control technologies for CE. It is a valuable resource for researchers and practitioners in multimedia analysis, human-computer interaction, and interactive user interfaces, as well as for graduate students studying computer vision and pattern recognition.
|15."Visual Attributes (Advances in Computer Vision and Pattern Recognition)" by Devi Parikh and Rogerio Schmidt Feris|
“Visual Attributes” Book Review: This book offers a comprehensive overview of the latest developments in machine learning and computer vision regarding visual attributes. It explores the intersection of this emerging field with other disciplines, such as computational linguistics and human-machine interaction. The book introduces attribute-based methods for zero-shot classification, privileged information learning, and multi-task attribute learning. It examines the concept of relative attributes and evaluates the effectiveness of modeling relative attributes in image search applications. The state-of-the-art methods for estimating human attributes and their use in various applications are also discussed. The book explores attempts to build a vocabulary of visual attributes and their connection to natural language. It features contributions from renowned scientists worldwide, covering both theoretical aspects and practical applications. The book is an essential resource for researchers and practitioners in the fields of machine learning, computer vision, and natural language processing, as well as graduate students interested in these topics.
|16."Graph Based Representations in Pattern Recognition" by Edwin Hancock and Mario Vento|
“Graph Based Representations in Pattern Recognition” Book Review: This book is about the sixth IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2007, which took place in Alicante, Spain in June 2007. The book contains 23 full papers and 14 poster papers that were selected from 54 submissions. The papers are organized into different sections, such as coordinating, distances and measures, chart-based division and image processing, chart-based grouping, chart representations, pyramids, combinatorial maps and homologies, as well as chart clustering, embedding and learning, to make them easier to understand.
|17."Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications (Advances in Computer Vision and Pattern Recognition)" by Hong Cheng|
“Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications (Advances in Computer Vision and Pattern Recognition)” Book Review: This comprehensive book is aimed at undergraduates, graduates, and research scholars of electrical and electronics engineering, as well as students of embedded systems and computer engineering. The book provides a thorough review of the state of the art in sparse representations, modeling, and learning, examining both the theoretical foundations and details of algorithm implementation. The book emphasizes the practical application of compressed sensing research in visual recognition and computer vision. It covers a range of topics, including sparse recovery approaches, robust and efficient sparse representation, large-scale visual recognition, feature representation and learning, sparsity-induced similarity, and sparse representation and learning-based classifiers. The book also discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning. Appendices outlining additional computer programming resources and explaining the essential mathematics required to understand the book are also included.
17 Best Books on Pattern Recognition
We have compiled a list of the Best Reference Books on Pattern Recognition, which are used by students of top universities, and colleges. This will help you choose the right book depending on if you are a beginner or an expert. Here is the complete list of Pattern Recognition Books with their authors, publishers, and an unbiased review of them as well as links to the Amazon website to directly purchase them. If permissible, you can also download the free PDF books on Pattern Recognition below.
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