Описание: This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis. The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book’s novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments; stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit; evaluation of HGFRNNs with different types of recurrent units; and adaptive assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.
Автор: Daniel Cremers; Bodo Rosenhahn; Alan L. Yuille; Fr Название: Statistical and Geometrical Approaches to Visual Motion Analysis ISBN: 3642030602 ISBN-13(EAN): 9783642030604 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: International Dagstuhl Seminar Dagstuhl Castle July 1318 2008 Revised Papers. .
Автор: Thomas B Moeslund; Название: Visual Analysis of Humans ISBN: 0857299964 ISBN-13(EAN): 9780857299963 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This unique text/reference provides a coherent and comprehensive overview of all aspects of video analysis of humans. Broad in coverage and accessible in style, the text presents original perspectives collected from preeminent researchers gathered from across the world. In addition to presenting state-of-the-art research, the book reviews the historical origins of the different existing methods, and predicts future trends and challenges. Features: with a Foreword by Professor Larry Davis; contains contributions from an international selection of leading authorities in the field; includes an extensive glossary; discusses the problems associated with detecting and tracking people through camera networks; examines topics related to determining the time-varying 3D pose of a person from video; investigates the representation and recognition of human and vehicular actions; reviews the most important applications of activity recognition, from biometrics and surveillance, to sports and driver assistance.
Instead of focusing on the mathematical properties of moments, this book is a compendium of research that demonstrates the effectiveness of orthogonal moment-based features in face recognition, expression recognition, fingerprint recognition and iris recognition.
The usefulness of moments and their invariants in pattern recognition is well known. What is less well known is how orthogonal moments may be applied to specific problems in human-centric visual pattern recognition. Unlike previous books, this work highlights the fundamental issues involved in moment-based pattern recognition, from the selection of discriminative features in a high-dimensional setting, to addressing the question of how to classify a large number of patterns based on small training samples. In addition to offering new concepts that illustrate the use of statistical methods in addressing some of these issues, the book presents recent results and provides guidance on implementing the methods. Accordingly, it will be of interest to researchers and graduate students working in the broad areas of computer vision and visual pattern recognition.
Автор: James J. (Jong Hyuk) Park; Qun Jin; Martin Sang-so Название: Human Centric Technology and Service in Smart Space ISBN: 9400795599 ISBN-13(EAN): 9789400795594 Издательство: Springer Рейтинг: Цена: 32004.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The theme of HumanCom is focused on the various aspects of human-centric computing for advances in computer science and its applications and provides an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of human-centric computing.
Автор: Jitao Sang Название: User-centric Social Multimedia Computing ISBN: 3662514915 ISBN-13(EAN): 9783662514917 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the first paradigm of social multimedia computing completely from the user perspective. Different from traditional multimedia and web multimedia computing which are content-centric, social multimedia computing rises under the participatory Web2.0 and is essentially user-centric.
Автор: Liming Chen and Chris D. Nugent Название: Human Activity Recognition and Behaviour Analysis ISBN: 3030194078 ISBN-13(EAN): 9783030194079 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Поставка под заказ.
Описание: It is also a valuable research reference resource for postdoctoral candidates and academics in relevant research and application domains, such as data analytics, smart cities, smart energy, and smart healthcare, to name but a few.
Автор: Zhou, Kevin Название: Deep Learning for Medical Image Analysis ISBN: 0128104082 ISBN-13(EAN): 9780128104088 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas.
Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis.
Автор: Fumiaki Tomita; Saburo Tsuji Название: Computer Analysis of Visual Textures ISBN: 1461288320 ISBN-13(EAN): 9781461288329 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents theories and techniques for perception of textures by computer. Texture analysis is one of the first important steps in computer vision since texture provides important cues to recognize real-world objects.
Автор: Chen Chen; Yuzhuo Ren; C.-C. Jay Kuo Название: Big Visual Data Analysis ISBN: 9811006296 ISBN-13(EAN): 9789811006296 Издательство: Springer Рейтинг: Цена: 9141.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoorscene classification, and outdoor scene layout estimation.
Автор: Tominski, Christian , Schumann, Heidrun Название: Interactive Visual Data Analysis ISBN: 0367898756 ISBN-13(EAN): 9780367898755 Издательство: Taylor&Francis Рейтинг: Цена: 9186.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book provides a comprehensive overview on information visualization and visual exploration. The top-down view on the problem illustrated with numerous examples based on real data and settings will help people from these domains to get a sound knowledge about key challenges, concepts and methodologies in this regard.
Автор: Yun Fu Название: Low-Rank and Sparse Modeling for Visual Analysis ISBN: 3319119990 ISBN-13(EAN): 9783319119991 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data.
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