Best Reference Books – Artificial Intelligence and Pattern Recognition

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We have compiled the list of Top 10 Best Reference Books on Artificial Intelligence and Pattern Recognition subject. These books are used by students of top universities, institutes and colleges. Here is the full list of top 10 best books on Artificial Intelligence and Pattern Recognition along with reviews.

Kindly note that we have put a lot of effort into researching the best books on Artificial Intelligence and Pattern Recognition subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "Artificial Intelligence and Pattern Recognition" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.

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 describes the pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. Probability distributions are described through graphic models. The book includes an introduction to basic probability theory so it is helpful for first time learners of the subject. It will be useful for postgraduate students studying machine learning in college. The short answer questions and multiple choice questions at the end of each chapter help the students to test their understanding of the subject.

2. “Pattern Recognition: Techniques and Applications” by Rajjan Shinghal

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“Pattern Recognition: Techniques and Applications” Book Review: This book provides a comprehensive coverage of the procedures for Pattern Recognition. It begins by introducing the concept of inductive learning. Other important topics such as feature selection and clustering are also included. The last chapter compares the results of classifying a given problem by each procedure, and proposes research on finding their underlying commonality. The book includes programming and non-programming exercises at the end of each chapter for the readers to test their understanding. It will benefit undergraduate and master’s Engineering students for the course on Pattern Recognition. It would also be a useful reference for practicing engineers in industrial and research organizations.

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: This book is a complete guide to markov models in pattern recognition. It includes a detailed description of the EM algorithm. The book also introduces an analysis of efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. A special emphasis is also placed on practical algorithmic solutions. The book covers a description of probability quantities and presents methods for the configuration of hidden Markov models for specific application areas. It is useful for researchers, practitioners, and graduate students of pattern recognition.

4. “NETLAB: Algorithms for Pattern Recognition (Advances in Computer Vision and Pattern Recognition)” by Ian T Nabney

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“NETLAB: Algorithms for Pattern Recognition (Advances in Computer Vision and Pattern Recognition)” Book Review: This book focuses on describing neural networks and related data modelling techniques. It emphasizes on teaching methods that are relevant to the practical application of neural networks and pattern analysis problems. The book includes examples and demonstration programs to illustrate the theory that helps the reader understand the algorithms and how to apply them. The readers get to learn how to use MATLAB for pattern recognition. The book will benefit teachers and students of undergraduate and postgraduate courses in pattern recognition. The topics are discussed along with examples to give a detailed understanding of the subject.

5. “Pattern Recognition” by Gerhard Rigoll

“Pattern Recognition” Book Review: This book is a compilation of the proceedings of the 30th Symposium of the German Association for Pattern Recognition. A total of 53 papers cover different topics. The topics are divided into sections to include learning and classification, tracking, medical image processing and segmentation. In addition, audio, speech and handwriting recognition, multiview geometry and 3D-reconstruction, motion and matching, and image analysis are also discussed. The book is a useful learning source for researchers, students and teachers in pattern recognition. It provides technical knowledge of the subject based on real-world applications.

6. “Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications (Advances in Computer Vision and Pattern Recognition)” by imusti

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“Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications (Advances in Computer Vision and Pattern Recognition)” Book Review: This comprehensive book presents the latest advances in applications of multimedia interaction and user interfaces for consumer electronics. It covers issues of multimedia content analysis and human-machine interaction. The book introduces topics such as novel computationally efficient algorithms to extract semantically meaningful audio-visual events. In addition, it takes into account the cognitive impacts of modality on human information processing and provides an overview on gesture control technologies for CE. The book is useful for researchers and practitioners in multimedia analysis, human-computer interaction and interactive user interfaces. Also useful for graduate students studying computer vision and pattern recognition.

7. “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: This book is a detailed study of speech recognition. It looks at fuzzy-set theory and artificial intelligence to find definitive solutions to the speech-recognition problem. The book provides a research analysis of making an experimental model capable of understanding spoken sentences of a natural language. For that purpose, it goes into the complexity of the functions performed by the human brain. The book introduces a method for conceiving modules performing perceptual tasks and for combining them in a speech understanding system. The book is useful for students and teachers of computer science and software engineering. It will also benefit researchers as it includes a thorough research in the field.

8. “A Structural Analysis of Complex Aerial Photographs (Advanced Applications in Pattern Recognition)” by Makoto Nagao and Takashi Matsuyama

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“A Structural Analysis of Complex Aerial Photographs (Advanced Applications in Pattern Recognition)” Book Review: This book presents a deep unification and synthesis of the two fundamental approaches to pat­tern recognition- numerical (or statistical) and struc­tural (linguistic or syntactic). The methodology adopted by the book is based on natural use of the knowledge-base framework. The structural analysis of complex aerial photographs is achieved through a systematic and practice-oriented approach. The topics are described with illustrations and examples that provide the readers with a practical understanding of the subject matter. The book is useful for practitioners working in the field of advanced systems in pattern recognition. It will also benefit students, teachers and researchers interested in the subject.

9. “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 presents a collection of computational intelligence algorithms. The focus is on addressing the issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape, etc. In the first part it describes research issues in the field with a survey of the related literature. The next part deals with computational intelligence based algorithms for feature selection and classification. The third part presents biologically inspired algorithms for feature extraction. Several figures, charts, tables and equations helping the reader to understand the material presented without instruction. The book is useful for teachers, students and practitioners in the field of pattern recognition.

10. “Automatic Speech Recognition on Mobile Devices and over Communication Networks (Advances in Computer Vision and Pattern Recognition)” by Zheng-Hua Tan

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“Automatic Speech Recognition on Mobile Devices and over Communication Networks (Advances in Computer Vision and Pattern Recognition)” Book Review: This book presents the issues in the field of advancement in computing and networking. It is a collection of papers about speech recognition, in particular on mobile and over-the-network systems. It also focuses on automatic speech recognition on mobile devices and over communication networks. The book begins with a comprehensive introduction to the subject of speech recognition in devices and networks. Then it goes on to study speech recognition systems- network, distributed and embedded speech recognition systems. The book is useful for researchers and engineers in the field of speech recognition.

People who are searching for Free downloads of books and free pdf copies of these top 10 books on Artificial Intelligence and Pattern Recognition – we would like to mention that we don’t have free downloadable pdf copies of these good books and one should look for free pdf copies from these Authors only if they have explicitly made it free to download and read them.

We have created a collection of best reference books on "Artificial Intelligence and Pattern Recognition" so that one can readily see the list of top books on "Artificial Intelligence and Pattern Recognition" and buy the books either online or offline.

If any more book needs to be added to the list of best books on Artificial Intelligence and Pattern Recognition subject, please let us know.

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Manish Bhojasia - Founder & CTO at Sanfoundry
Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @ LinkedIn | Youtube | Instagram | Facebook | Twitter