
- Author : Santosh Kumar
- Publsiher : Academic Press
- Release : 15 May 2021
- ISBN : 9780128237373
- Pages : 375 pages
- Rating : 4/5 from 21 reviews
Read or download book entitled Multimodal Machine Learning written by Santosh Kumar which was release on 15 May 2021, this book published by Academic Press. Available in PDF, EPUB and Kindle Format. Book excerpt: Multimodal Machine Learning: Techniques and Applications explains recent advances in multimodal machine learning, providing a coherent set of fundamentals for designing efficient multimodal learning algorithms for different applications. The book addresses the main challenges in multimodal machine learning based computing paradigms, including multimodal representation learning, translation and mapping, modality alignment, multimodal fusion and co-learning. The book also explores the important texture feature descriptors based on recognition and transform techniques. It is ideal for senior undergraduates, graduate students, and researchers in data science, engineering, computer science and statistics. Presents new representation, classification and identification algorithms for data prediction and analysis on feature characteristics Discusses recent and future advancements in diversified fields of computer vision , pattern recognition, generative adversarial network-based learning, video analytics and data science Provides an overview of future research challenges and directions
Summary : Multimodal Machine Learning: Techniques and Applications explains recent advances in multimodal machine learning, providing a coherent set of fundamentals for designing efficient multimodal learning algorithms for different applications. The book addresses the main challenges in multimodal machine learning based computing paradigms, including multimodal representation learning, translation and mapping, modality alignment, ...
Summary : This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Machine Learning for Multimodal Interaction, MLMI 2004, held in Martigny, Switzerland in June 2004. The 30 revised full papers presented were carefully selected during two rounds of reviewing and revision. The papers are organized in topical sections on HCI and ...
Summary : Markus Kächele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He focuses on multimodal recognition of discrete and continuous ...
Summary : TheseriesofworkshopsonMachineLearningforMultimodalInteraction(MLMI) celebratesthisyearits?fthanniversary.Onthisoccasion,anumberofinnovations havebeenintroducedin the reviewingandpublicationprocedures,while keeping the focus onthe samescienti?c topics. For the ?rst time, the reviewing process has been adapted in order to p- parethe proceedings in time for the workshop,held on September 8–10,2008,in Utrecht, The Netherlands. The 47 submissions received by the ...
Summary : Download or read online Multimodal Machine Learning for Intelligent Mobility written by Jamie Roche, published by which was released on 2020. Get Multimodal Machine Learning for Intelligent Mobility Books now! Available in PDF, ePub and Kindle....
Summary : Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The ...
Summary : This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, ...
Summary : This book focuses on various advanced technologies which integrate with machine learning to assist one of the most leading industries, healthcare. It presents recent research works based on machine learning approaches supported by medical and information communication technologies with the use of data and image analysis. The book presents insight ...
Summary : The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international ...
Summary : This book aims to explore and discuss theories and technologies for the development of socially competent and culture-aware embodied conversational agents for elderly care. To tackle the challenges in ageing societies, this book was written by experts who have a background in assistive technologies for elderly care, culture-aware computing, multimodal ...
Summary : This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Machine Learning for Multimodal Interaction, MLMI 2006, held in Bethesda, MD, USA, in May 2006. The papers are organized in topical sections on multimodal processing, image and video processing, HCI and applications, discourse and dialogue, speech and audio processing, ...
Summary : The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces-user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces. This three-volume handbook is written by international experts and pioneers in the ...
Summary : This book aims to provide an overview of theoretical and practical considerations in terms of self-directed multimodal learning within the university context. Multimodal learning is approached in terms of the levels of multimodality and specifically blended learning and the mixing of modes of delivery (contact and distance education). As such, ...
Summary : This book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. ...
Summary : This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal ...