IoT Sensor-Based Activity Recognition, Ahad, Md Atiqur Rahman, Antar, Anindya Das, Ahmed,

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Автор: Jorge Luis Reyes Ortiz
Название: Smartphone-Based Human Activity Recognition
ISBN: 3319367706 ISBN-13(EAN): 9783319367705
Издательство: Springer
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Цена: 95770.00 T
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Описание: The book reports on the author`s original work to address the use of today`s state-of-the-art smartphones for human physical activity recognition.

Автор: Yun Fu
Название: Human Activity Recognition and Prediction
ISBN: 3319270028 ISBN-13(EAN): 9783319270029
Издательство: Springer
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Цена: 74530.00 T
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Описание: This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos.

Автор: Jorge Luis Reyes Ortiz
Название: Smartphone-Based Human Activity Recognition
ISBN: 3319142739 ISBN-13(EAN): 9783319142739
Издательство: Springer
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Цена: 121890.00 T
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Описание: The book reports on the author`s original work to address the use of today`s state-of-the-art smartphones for human physical activity recognition.

Автор: Liming Chen; Chris D. Nugent; Jit Biswas; Jesse Ho
Название: Activity Recognition in Pervasive Intelligent Environments
ISBN: 9491216406 ISBN-13(EAN): 9789491216404
Издательство: Springer
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Цена: 111790.00 T
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Описание: The fourth category of topic will be dedicated to representative applications of activity recognition in intelligent environments, which address the life cycle of activity recognition and their use for novel functions of the end-user systems with comprehensive implementation, prototyping and evaluation.

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
Наличие на складе: Невозможна поставка.
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: Jacek Grekow
Название: From Content-based Music Emotion Recognition to Emotion Maps of Musical Pieces
ISBN: 331970608X ISBN-13(EAN): 9783319706085
Издательство: Springer
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Цена: 111790.00 T
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Описание: Further, it explores emotion detection in MIDI and audio files. In the experiments presented here, the categorical and dimensional approaches were used, and the knowledge and expertise of music experts with a university music education were used for music file annotation.

Автор: Masakazu Iwamura; Faisal Shafait
Название: Camera-Based Document Analysis and Recognition
ISBN: 3319051660 ISBN-13(EAN): 9783319051666
Издательство: Springer
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Цена: 58690.00 T
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Описание: This book constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2013, held in Washington, DC, USA, in August 2013.

Автор: Edwin Hancock; Marcello Pelillo
Название: Similarity-Based Pattern Recognition
ISBN: 3642391397 ISBN-13(EAN): 9783642391392
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book constitutes the proceedings of the Second International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2013, which was held in York, UK, in July 2013.

Автор: Jacek Grekow
Название: From Content-based Music Emotion Recognition to Emotion Maps of Musical Pieces
ISBN: 3319889680 ISBN-13(EAN): 9783319889689
Издательство: Springer
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Цена: 111790.00 T
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Описание: The problems it addresses include emotion representation, annotation of music excerpts, feature extraction, and machine learning. The book chiefly focuses on content-based analysis of music files, a system that automatically analyzes the structures of a music file and annotates the file with the perceived emotions. Further, it explores emotion detection in MIDI and audio files. In the experiments presented here, the categorical and dimensional approaches were used, and the knowledge and expertise of music experts with a university music education were used for music file annotation. The automatic emotion detection systems constructed and described in the book make it possible to index and subsequently search through music databases according to emotion. In turn, the emotion maps of musical compositions provide valuable new insights into the distribution of emotions in music and can be used to compare that distribution in different compositions, or to conduct emotional comparisons of different interpretations of the same composition.

Автор: Donatello Conte; Jean-Yves Ramel; Pasquale Foggia
Название: Graph-Based Representations in Pattern Recognition
ISBN: 3030200809 ISBN-13(EAN): 9783030200800
Издательство: Springer
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Цена: 54030.00 T
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Описание: They cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph embedding, spectral graph problems, and parallel algorithms for graph problems.

Автор: Xiaochun Wang; Xiali Wang; Don Mitchell Wilkes
Название: Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment
ISBN: 9811392161 ISBN-13(EAN): 9789811392160
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene recognition. The respective chapters highlight the latest developments in vision-based machine perception and machine learning research for localization applications, and cover such topics as: image-segmentation-based visual perceptual grouping for the efficient identification of objects composing unknown environments; classification-based rapid object recognition for the semantic analysis of natural scenes in unknown environments; the present understanding of the Prefrontal Cortex working memory mechanism and its biological processes for human-like localization; and the application of this present understanding to improve mobile robot localization. The book also features a perspective on bridging the gap between feature representations and decision-making using reinforcement learning, laying the groundwork for future advances in mobile robot navigation research.