Reproducible Research in Pattern Recognition, Bertrand Kerautret; Miguel Colom; Daniel Lopresti;

Автор: Strang Gilbert
Название: Linear Algebra and Learning from Data
ISBN: 0692196382 ISBN-13(EAN): 9780692196380
Издательство: Cambridge Academ
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Цена: 66520.00 T
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Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

Автор: Shalev-Shwartz
Название: Understanding Machine Learning
ISBN: 1107057132 ISBN-13(EAN): 9781107057135
Издательство: Cambridge Academ
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Цена: 74630.00 T
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Описание: Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. This book explains the principles behind the automated learning approach and the considerations underlying its usage. The authors explain the `hows` and `whys` of machine-learning algorithms, making the field accessible to both students and practitioners.

Автор: Thomas Lu, Tien-Hsin Chao
Название: Advances in Pattern Recognition Research
ISBN: 1536144290 ISBN-13(EAN): 9781536144291
Издательство: Nova Science
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Цена: 215410.00 T
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Описание: 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.

Автор: Dancygier
Название: The Cambridge Handbook of Cognitive Linguistics
ISBN: 1107118441 ISBN-13(EAN): 9781107118447
Издательство: Cambridge Academ
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Цена: 162630.00 T
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Описание: A comprehensive survey of the quickly developing discipline of cognitive linguistics, its rich methodology, key results, and interdisciplinary context. Providing an accessible overview of research questions, basic concepts, and various theoretical approaches, the Handbook places linguistic facts in the context of gesture studies, neuroscience, computational approaches, and many other fields.

Автор: Bishop, Christopher M.
Название: Neural Networks for Pattern Recognition
ISBN: 0198538642 ISBN-13(EAN): 9780198538646
Издательство: Oxford Academ
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Цена: 92930.00 T
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Описание: This book is the first to provide a comprehensive account of neural networks from a statistical perspective. Its emphasis is on pattern recognition, which currently represents the area of greatest applicability for neural networks. By focusing on pattern recognition, the book provides a much more extensive treatment of many topics than is available in earlier books.

Автор: Boyd Stephen
Название: Introduction to Applied Linear Algebra
ISBN: 1316518965 ISBN-13(EAN): 9781316518960
Издательство: Cambridge Academ
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Цена: 45410.00 T
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Описание: A groundbreaking introductory textbook covering the linear algebra methods needed for data science and engineering applications. It combines straightforward explanations with numerous practical examples and exercises from data science, machine learning and artificial intelligence, signal and image processing, navigation, control, and finance.

Автор: Walter J. Scheirer
Название: Extreme Value Theory-Based Methods for Visual Recognition
ISBN: 1627057005 ISBN-13(EAN): 9781627057004
Издательство: Turpin
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Цена: 68930.00 T
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Описание: A common feature of many approaches to modeling sensory statistics is an emphasis on capturing the ""average."" From early representations in the brain, to highly abstracted class categories in machine learning for classification tasks, central-tendency models based on the Gaussian distribution are a seemingly natural and obvious choice for modeling sensory data. However, insights from neuroscience, psychology, and computer vision suggest an alternate strategy: preferentially focusing representational resources on the extremes of the distribution of sensory inputs. The notion of treating extrema near a decision boundary as features is not necessarily new, but a comprehensive statistical theory of recognition based on extrema is only now just emerging in the computer vision literature. This book begins by introducing the statistical Extreme Value Theory (EVT) for visual recognition. In contrast to central-tendency modeling, it is hypothesized that distributions near decision boundaries form a more powerful model for recognition tasks by focusing coding resources on data that are arguably the most diagnostic features. EVT has several important properties: strong statistical grounding, better modeling accuracy near decision boundaries than Gaussian modeling, the ability to model asymmetric decision boundaries, and accurate prediction of the probability of an event beyond our experience. The second part of the book uses the theory to describe a new class of machine learning algorithms for decision making that are a measurable advance beyond the state-of-the-art. This includes methods for post-recognition score analysis, information fusion, multi-attribute spaces, and calibration of supervised machine learning algorithms.

Автор: Shouvik Chakraborty, Kalyani Mali
Название: Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities
ISBN: 1799827372 ISBN-13(EAN): 9781799827375
Издательство: Mare Nostrum (Eurospan)
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Цена: 134910.00 T
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Описание: Computer vision and object recognition are two technological methods that are frequently used in various professional disciplines. In order to maintain high levels of quality and accuracy of services in these sectors, continuous enhancements and improvements are needed. The implementation of artificial intelligence and machine learning has assisted in the development of digital imaging, yet proper research on the applications of these advancing technologies is lacking.

Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities explores the theoretical and practical aspects of modern advancements in digital image analysis and object detection as well as its applications within healthcare, security, and engineering fields. Featuring coverage on a broad range of topics such as disease detection, adaptive learning, and automated image segmentation, this book is ideally designed for engineers, physicians, researchers, academicians, practitioners, scientists, industry professionals, scholars, and students seeking research on the current developments in object recognition using artificial intelligence.

Автор: Shouvik Chakraborty, Kalyani Mali
Название: Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities
ISBN: 1799827364 ISBN-13(EAN): 9781799827368
Издательство: Mare Nostrum (Eurospan)
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Цена: 174630.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computer vision and object recognition are two technological methods that are frequently used in various professional disciplines. In order to maintain high levels of quality and accuracy of services in these sectors, continuous enhancements and improvements are needed. The implementation of artificial intelligence and machine learning has assisted in the development of digital imaging, yet proper research on the applications of these advancing technologies is lacking.

Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities explores the theoretical and practical aspects of modern advancements in digital image analysis and object detection as well as its applications within healthcare, security, and engineering fields. Featuring coverage on a broad range of topics such as disease detection, adaptive learning, and automated image segmentation, this book is ideally designed for engineers, physicians, researchers, academicians, practitioners, scientists, industry professionals, scholars, and students seeking research on the current developments in object recognition using artificial intelligence.

Автор: Larisa Angstenberger
Название: Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering
ISBN: 9048157757 ISBN-13(EAN): 9789048157754
Издательство: Springer
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Цена: 153720.00 T
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Описание: Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition.

Автор: B B Chaudhuri
Название: Advances in Digital Document Processing and Retrieval
ISBN: 9814368709 ISBN-13(EAN): 9789814368704
Издательство: World Scientific Publishing
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Цена: 118270.00 T
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Описание: Suitable for both students and researchers working on various aspects of document image analysis and recognition problems, this title covers such topics as: Going beyond the Myth of Paperlessness, The Role of Document Image Analysis in Trustworthy Elections as well as Word Recognition for Museum Index Cards with SNT-Grid.

Автор: Shutao Li; Chenglin Liu; Yaonan Wang
Название: Pattern Recognition
ISBN: 3662456427 ISBN-13(EAN): 9783662456422
Издательство: Springer
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Цена: 83850.00 T
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Описание: The two-volume set CCIS 483 and CCIS 484 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition, CCPR 2014, held in Changsha, China, in November 2014. The papers are organized in topical sections on fundamentals of pattern recognition; image processing and analysis; video processing and analysis;