Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support, Kenji Suzuki; Mauricio Reyes; Tanveer Syeda-Mahmoo
Автор: Tam?s Kenesei; J?nos Abonyi Название: Interpretability of Computational Intelligence-Based Regression Models ISBN: 3319219413 ISBN-13(EAN): 9783319219417 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The key idea of this book is that hinging hyperplanes, neural networks and support vector machines can be transformed into fuzzy models, and interpretability of the resulting rule-based systems can be ensured by special model reduction and visualization techniques.
This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.
The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.
Автор: Nie Liqiang, Liu Meng, Song Xuemeng Название: Multimodal Learning toward Micro-Video Understanding ISBN: 1681736306 ISBN-13(EAN): 9781681736303 Издательство: Mare Nostrum (Eurospan) Цена: 103490.00 T Наличие на складе: Нет в наличии. Описание:
Micro-videos, a new form of user-generated content, have been spreading widely across various social platforms, such as Vine, Kuaishou, and TikTok.
Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to their brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for high-order micro-video understanding.
Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of venue categories to guide micro-video analysis; (3) how to alleviate the influence of low quality caused by complex surrounding environments and camera shake; (4) how to model multimodal sequential data, i.e. textual, acoustic, visual, and social modalities to enhance micro-video understanding; and (5) how to construct large-scale benchmark datasets for analysis. These challenges have been largely unexplored to date.
In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.
Автор: Nie Liqiang, Liu Meng, Song Xuemeng Название: Multimodal Learning toward Micro-Video Understanding ISBN: 1681736284 ISBN-13(EAN): 9781681736280 Издательство: Mare Nostrum (Eurospan) Цена: 82230.00 T Наличие на складе: Нет в наличии. Описание:
Micro-videos, a new form of user-generated content, have been spreading widely across various social platforms, such as Vine, Kuaishou, and TikTok.
Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to their brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for high-order micro-video understanding.
Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of venue categories to guide micro-video analysis; (3) how to alleviate the influence of low quality caused by complex surrounding environments and camera shake; (4) how to model multimodal sequential data, i.e. textual, acoustic, visual, and social modalities to enhance micro-video understanding; and (5) how to construct large-scale benchmark datasets for analysis. These challenges have been largely unexplored to date.
In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.
Автор: Henning M?ller; Oscar Alfonso Jimenez del Toro; Al Название: Multimodal Retrieval in the Medical Domain ISBN: 3319244701 ISBN-13(EAN): 9783319244709 Издательство: Springer Рейтинг: Цена: 37270.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the First International Workshop on Multimodal Retrieval in the Medical Domain, MRMD 2015, held in Vienna, Austria, on March 29, 2015.
Автор: Danail Stoyanov; Zeike Taylor; Gustavo Carneiro; T Название: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support ISBN: 3030008886 ISBN-13(EAN): 9783030008888 Издательство: Springer Рейтинг: Цена: 61480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed joint proceedings of the 4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018, and the 8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018.The 39 full papers presented at DLMIA 2018 and the 4 full papers presented at ML-CDS 2018 were carefully reviewed and selected from 85 submissions to DLMIA and 6 submissions to ML-CDS. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.
Автор: Quanzheng Li; Richard Leahy; Bin Dong; Xiang Li Название: Multiscale Multimodal Medical Imaging ISBN: 303037968X ISBN-13(EAN): 9783030379681 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the First International Workshop on Multiscale Multimodal Medical Imaging, MMMI 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019. The 13 papers presented were carefully reviewed and selected from 18 submissions.
Автор: Andrei Popescu-Belis; Rainer Stiefelhagen Название: Machine Learning for Multimodal Interaction ISBN: 3540858520 ISBN-13(EAN): 9783540858522 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Constitutes the refereed proceedings of the 5th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2008, held in Utrecht, The Netherlands, in September 2008. This title features papers that cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction.
Автор: Ronald B?ck; Francesca Bonin; Nick Campbell; Ronal Название: Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction ISBN: 3319155563 ISBN-13(EAN): 9783319155562 Издательство: Springer Рейтинг: Цена: 37270.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Annotating the TCD D-ANS Corpus - A Multimodal Multimedia Monolingual Biometric Corpus of Spoken Social Interaction.- Steps Towards More Natural Human-Machine Interaction via Audio-Visual Word Prominence Detection.- Improving Robustness Against Environmental Sounds for Directing Attention of Social Robots.- On Annotation and Evaluation of Multi-modal Corpora in Affective Human-Computer Interaction.- Modelling User Experience in Human-Robot Interactions.- Disposition Recognition from Spontaneous Speech Towards a Combination with Co-speech Gestures.- ASR Independent Hybrid Recurrent Neural Network Based Error Correction for Dialog System Applications.- Acquisition and Use of Long-Term Memory for Personalized Dialog Systems.- An Automatic Shout Detection System Using Speech Production Features.- Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose.- A Multimodal Multimedia Monolingual Biometric Corpus of Spoken Social Interaction.- Steps Towards More Natural Human-Machine Interaction via Audio-Visual Word Prominence Detection.- Improving Robustness Against Environmental Sounds for Directing Attention of Social Robots.- On Annotation and Evaluation of Multi-modal Corpora in Affective Human-Computer Interaction.- Modelling User Experience in Human-Robot Interactions.-Disposition Recognition from Spontaneous Speech Towards a Combination with Co-speech Gestures.- ASR Independent Hybrid Recurrent Neural Network Based Error Correction for Dialog System Applications.- Acquisition and Use of Long-Term Memory for Personalized Dialog Systems.- An Automatic Shout Detection System Using Speech Production Features.- Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose.
Автор: Angel D. Sappa; Jordi Vitri? Название: Multimodal Interaction in Image and Video Applications ISBN: 3642359310 ISBN-13(EAN): 9783642359316 Издательство: Springer Рейтинг: Цена: 130610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book shows case studies of multimodal interactive technologies for both image and video applications. They cover a wide spectrum of applications, ranging from interactive handwriting transcriptions to human-robot interactions in real environments.
Автор: Angel D. Sappa; Jordi Vitri? Название: Multimodal Interaction in Image and Video Applications ISBN: 3642439837 ISBN-13(EAN): 9783642439834 Издательство: Springer Рейтинг: Цена: 113180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book shows case studies of multimodal interactive technologies for both image and video applications. They cover a wide spectrum of applications, ranging from interactive handwriting transcriptions to human-robot interactions in real environments.
Автор: Gavrilova & Monwar Название: Multimodal Biometrics And Intelligent Image Processing For Security System ISBN: 1466636467 ISBN-13(EAN): 9781466636460 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 189420.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Although it is a relatively new approach to biometric knowledge representation, multimodal biometric systems have emerged as an innovative alternative that aids in developing a more reliable and efficient security system. <br><br><em>Multimodal Biometrics and Intelligent Image Processing for Security Systems</em> provides an in-depth description of existing and fresh fusion approaches for multimodal biometric systems. Covering relevant topics affecting the security and intelligent industries, this reference will be useful for readers from both academia and industry in the areas of pattern recognition, security, and image processing domains.
Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2) ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
