Feature Extraction and Classification Techniques for Text Recognition, Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, R. K. Sharma, Anupam Garg
Автор: Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, R. K. Sharma, Anupam Garg Название: Feature Extraction and Classification Techniques for Text Recognition ISBN: 1799824063 ISBN-13(EAN): 9781799824060 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 257790.00 T Наличие на складе: Нет в наличии. Описание: Presents innovative research on the fusion and hybridization of various features and classifiers for document analysis and recognition. The book highlights a range of topics, including adaptive boosting, writer identification, and signature verification.
Автор: Jyotismita Chaki; Nilanjan Dey Название: Texture Feature Extraction Techniques for Image Recognition ISBN: 9811508526 ISBN-13(EAN): 9789811508523 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based.
Автор: Florian Eyben Название: Real-time Speech and Music Classification by Large Audio Feature Space Extraction ISBN: 3319272985 ISBN-13(EAN): 9783319272986 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book reports on an outstanding thesis thathas significantly advanced the state-of-the-art in the automated analysis andclassification of speech and music.
Автор: Nixon Mark Название: Feature Extraction and Image Processing for Computer Vision ISBN: 0128149760 ISBN-13(EAN): 9780128149768 Издательство: Elsevier Science Рейтинг: Цена: 77420.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the link between theory and exemplar code of the algorithms." Essential background theory is carefully explained.
This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation.
The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods
A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning
Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour)
Good balance between providing a mathematical background and practical implementation
Detailed and explanatory of algorithms in MATLAB and Python
Автор: Y-h. Taguchi Название: Unsupervised Feature Extraction Applied to Bioinformatics ISBN: 3030224554 ISBN-13(EAN): 9783030224554 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Поставка под заказ. Описание: This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available. The author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tenor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics.
Allows readers to analyze data sets with small samples and many features;Provides a fast algorithm, based upon linear algebra, to analyze big data;Includes several applications to multi-view data analyses, with a focus on bioinformatics.
Автор: Isabelle Guyon; Steve Gunn; Masoud Nikravesh; Loft Название: Feature Extraction ISBN: 366251771X ISBN-13(EAN): 9783662517710 Издательство: Springer Рейтинг: Цена: 278580.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction. Until now there has been insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons.
Автор: Ali Ismail Awad; Mahmoud Hassaballah Название: Image Feature Detectors and Descriptors ISBN: 3319288520 ISBN-13(EAN): 9783319288529 Издательство: Springer Рейтинг: Цена: 139310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This bookprovides readers with a selection of high-quality chapters that cover boththeoretical concepts and practical applications of image feature detectors anddescriptors. It serves as reference for researchers and practitioners byfeaturing survey chapters and research contributions on image feature detectorsand descriptors.
Автор: K. Sreenivasa Rao; Manjunath K E Название: Speech Recognition Using Articulatory and Excitation Source Features ISBN: 3319492195 ISBN-13(EAN): 9783319492193 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features.
Автор: K. Sreenivasa Rao; Shashidhar G. Koolagudi Название: Robust Emotion Recognition using Spectral and Prosodic Features ISBN: 1461463599 ISBN-13(EAN): 9781461463597 Издательство: Springer Рейтинг: Цена: 60940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner.
Автор: Kumar S. Ray Название: Soft Computing Approach to Pattern Classification and Object Recognition ISBN: 1489990100 ISBN-13(EAN): 9781489990105 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Soft Computing Approach to Pattern Classification and Object Recognition establishes an innovative, unified approach to supervised pattern classification and model-based occluded object recognition.
Автор: Volna Eva, Kotyrba Martin, Janosek Michal Название: Pattern Recognition and Classification in Time Series Data ISBN: 1522505652 ISBN-13(EAN): 9781522505655 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 180180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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.
Автор: Geoff Dougherty Название: Pattern Recognition and Classification ISBN: 1493953354 ISBN-13(EAN): 9781493953356 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume, both comprehensive and accessible, introduces all the key concepts in pattern recognition, and includes many examples and exercises that make it an ideal guide to an important methodology widely deployed in today`s ubiquitous automated systems.
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