Описание: This book constitutes the refereed post-conference proceedings of the 22nd Iberoamerican Congress on Pattern Recognition, CIARP 2017, held in Valparaiso, Chile, in November 2017. The 87 papers presented were carefully reviewed and selected from 156 submissions.
Описание: The papers are organized in topical sections on mathematical theory of PR, supervised and unsupervised classification, feature or instance selection for classification, image analysis and retrieval, signals analysis and processing, applications of pattern recognition, biometrics, video analysis, and data mining.
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: Christian Keimel Название: Design of Video Quality Metrics with Multi-Way Data Analysis ISBN: 9811002681 ISBN-13(EAN): 9789811002687 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- Video Quality.- Video Quality Metrics.- Data Analysis Approach.- Two-way Data Analysis.- Multi-way Data Analysis.- Model Building Considerations.- Designing Video Quality Metrics.- Performance Comparison.- Conclusion.
Автор: Herrera Francisco, Charte Francisco, Rivera Antonio J. Название: Multilabel Classification: Problem Analysis, Metrics and Techniques ISBN: 3319822691 ISBN-13(EAN): 9783319822693 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- Multilabel Classification.- Case Studies and Metrics.- Transformation based Classifiers.- Adaptation based Classifiers.- Ensemble based Classifiers.- Dimensionality Reduction.- Imbalance in Multilabel Datasets.- Multilabel Software.
Описание: This book constitutes the refereed conference proceedings of the 24rd Iberoamerican Congress on Pattern Recognition, CIARP 2019, held in Havana, Cuba, in October 2019. The 70 papers presented were carefully reviewed and selected from 128 submissions. Mathematical Theory of Pattern Recognition;
Автор: Amar Mitiche; J.K. Aggarwal Название: Computer Vision Analysis of Image Motion by Variational Methods ISBN: 3319007106 ISBN-13(EAN): 9783319007106 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a unified view of image motion analysis under the variational framework. It addresses the four core subjects of motion analysis: motion estimation, detection, tracking, and three-dimensional interpretation.
Описание: Artificial Intelligence (AI) is penetrating in all sciences as a multidisciplinary approach. However, adopting the theory of AI including computer vision and computer audition to urban intellectual space, is always difficult for architecture and urban planners. This book overcomes this challenge through a conceptual framework by merging computer vision and audition to urban studies based on a series of workshops called Remorph, conducted by Tehran Urban Innovation Center (TUIC).
Автор: Antonio Criminisi; J Shotton Название: Decision Forests for Computer Vision and Medical Image Analysis ISBN: 144716962X ISBN-13(EAN): 9781447169628 Издательство: Springer Рейтинг: Цена: 17468.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This practical, easy-to-follow book reviews the theoretical underpinnings of decision forests, organizing the existing literature in a new, general-purpose forest model. Includes exercises and experiments; slides, videos and more reside at a companion website.
Автор: Mousumi Gupta; Debanjan Konar; Siddhartha Bhattach Название: Computer Vision and Machine Intelligence in Medical Image Analysis ISBN: 9811387974 ISBN-13(EAN): 9789811387975 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book includes high-quality papers presented at the Symposium 2019, organised by Sikkim Manipal Institute of Technology (SMIT), in Sikkim from 26–27 February 2019. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.
Автор: Xingni Zhou, Zhiyuan Ren, Yanzhuo Ma, Kai Fan, Ji Xiang Название: Data structures based on linear relations ISBN: 3110595575 ISBN-13(EAN): 9783110595574 Издательство: Walter de Gruyter Цена: 12078.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Data structures is a key course for computer science and related majors. This book presents a variety of practical or engineering cases and derives abstract concepts from concrete problems. Besides basic concepts and analysis methods, it introduces basic data types such as sequential list, tree as well as graph. This book can be used as an undergraduate textbook, as a training textbook or a self-study textbook for engineers.
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