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Author: Jianwei Zhang Publisher: Frontiers Media SA ISBN: 2889762548 Category : Science Languages : en Pages : 295
Book Description
The purpose of this Research Topic is to reflect and discuss links between neuroscience, psychology, computer science and robotics with regards to the topic of cross-modal learning which has, in recent years, emerged as a new area of interdisciplinary research. The term cross-modal learning refers to the synergistic synthesis of information from multiple sensory modalities such that the learning that occurs within any individual sensory modality can be enhanced with information from one or more other modalities. Cross-modal learning is a crucial component of adaptive behavior in a continuously changing world, and examples are ubiquitous, such as: learning to grasp and manipulate objects; learning to walk; learning to read and write; learning to understand language and its referents; etc. In all these examples, visual, auditory, somatosensory or other modalities have to be integrated, and learning must be cross-modal. In fact, the broad range of acquired human skills are cross-modal, and many of the most advanced human capabilities, such as those involved in social cognition, require learning from the richest combinations of cross-modal information. In contrast, even the very best systems in Artificial Intelligence (AI) and robotics have taken only tiny steps in this direction. Building a system that composes a global perspective from multiple distinct sources, types of data, and sensory modalities is a grand challenge of AI, yet it is specific enough that it can be studied quite rigorously and in such detail that the prospect for deep insights into these mechanisms is quite plausible in the near term. Cross-modal learning is a broad, interdisciplinary topic that has not yet coalesced into a single, unified field. Instead, there are many separate fields, each tackling the concerns of cross-modal learning from its own perspective, with currently little overlap. We anticipate an accelerating trend towards integration of these areas and we intend to contribute to that integration. By focusing on cross-modal learning, the proposed Research Topic can bring together recent progress in artificial intelligence, robotics, psychology and neuroscience.
Author: Jianwei Zhang Publisher: Frontiers Media SA ISBN: 2889762548 Category : Science Languages : en Pages : 295
Book Description
The purpose of this Research Topic is to reflect and discuss links between neuroscience, psychology, computer science and robotics with regards to the topic of cross-modal learning which has, in recent years, emerged as a new area of interdisciplinary research. The term cross-modal learning refers to the synergistic synthesis of information from multiple sensory modalities such that the learning that occurs within any individual sensory modality can be enhanced with information from one or more other modalities. Cross-modal learning is a crucial component of adaptive behavior in a continuously changing world, and examples are ubiquitous, such as: learning to grasp and manipulate objects; learning to walk; learning to read and write; learning to understand language and its referents; etc. In all these examples, visual, auditory, somatosensory or other modalities have to be integrated, and learning must be cross-modal. In fact, the broad range of acquired human skills are cross-modal, and many of the most advanced human capabilities, such as those involved in social cognition, require learning from the richest combinations of cross-modal information. In contrast, even the very best systems in Artificial Intelligence (AI) and robotics have taken only tiny steps in this direction. Building a system that composes a global perspective from multiple distinct sources, types of data, and sensory modalities is a grand challenge of AI, yet it is specific enough that it can be studied quite rigorously and in such detail that the prospect for deep insights into these mechanisms is quite plausible in the near term. Cross-modal learning is a broad, interdisciplinary topic that has not yet coalesced into a single, unified field. Instead, there are many separate fields, each tackling the concerns of cross-modal learning from its own perspective, with currently little overlap. We anticipate an accelerating trend towards integration of these areas and we intend to contribute to that integration. By focusing on cross-modal learning, the proposed Research Topic can bring together recent progress in artificial intelligence, robotics, psychology and neuroscience.
Author: Manuel Diaz-Campos Publisher: John Wiley & Sons ISBN: 1119839831 Category : Language Arts & Disciplines Languages : en Pages : 628
Book Description
The Handbook of Usage-Based Linguistics The Handbook of Usage-Based Linguistics is the first edited volume to provide a comprehensive, authoritative, and interdisciplinary view of usage-based theory in linguistics. Contributions by an international team of established and emerging scholars discuss the application of used-based approaches in phonology, morphosyntax, psycholinguistics, language variation and change, language development, cognitive linguistics, and other subfields of linguistics. Unprecedented in depth and scope, this groundbreaking work of scholarship addresses all major theoretical and methodological aspects of usage-based linguistics while offering diverse perspectives and key insights into theory, history, and methodology. Throughout the text, in-depth essays explore up-to-date methodologies, emerging approaches, new technologies, and cutting-edge research in usage-based linguistics in many languages and subdisciplines. Topics include used-based approaches to subfields such as anthropological linguistics, computational linguistics, statistical analysis, and corpus linguistics. Covering the conceptual foundations, historical development, and future directions of usage-based theory, The Handbook of Usage-Based Linguistics is a must-have reference work for advanced students and scholars in anthropological linguistics, psycholinguistics, cognitive linguistics, corpora analysis, and other subfields of linguistics.
Author: Hayit Greenspan Publisher: Springer Nature ISBN: 3031439872 Category : Computers Languages : en Pages : 850
Book Description
The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learning – explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications – abdomen; clinical applications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular; Part VIII: Clinical applications – neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration.
Author: Yingmin Jia Publisher: Springer Nature ISBN: 9819968860 Category : Technology & Engineering Languages : en Pages : 850
Book Description
This book constitutes the proceedings of the 19th Chinese Intelligent Systems Conference, CISC 2023, which was held during October 14–15, 2023, in Ningbo, Zhejiang, China. The book focuses on new theoretical results and techniques in the field of intelligent systems and control. This is achieved by providing in-depth studies of a number of important topics such as multi-agent systems, complex networks, intelligent robots, complex systems theory and swarm behavior, event-driven and data-driven control, robust and adaptive control, big data and brain science, process control, intelligent sensors and detection technology, deep learning and learning control, navigation and control of aerial vehicles, and so on. The book is particularly suitable for readers interested in learning intelligent systems and control and artificial intelligence. The book can benefit researchers, engineers and graduate students.
Author: Lei Wang Publisher: Springer Nature ISBN: 3031263138 Category : Computers Languages : en Pages : 663
Book Description
The 7-volume set of LNCS 13841-13847 constitutes the proceedings of the 16th Asian Conference on Computer Vision, ACCV 2022, held in Macao, China, December 2022. The total of 277 contributions included in the proceedings set was carefully reviewed and selected from 836 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; optimization methods; Part II: applications of computer vision, vision for X; computational photography, sensing, and display; Part III: low-level vision, image processing; Part IV: face and gesture; pose and action; video analysis and event recognition; vision and language; biometrics; Part V: recognition: feature detection, indexing, matching, and shape representation; datasets and performance analysis; Part VI: biomedical image analysis; deep learning for computer vision; Part VII: generative models for computer vision; segmentation and grouping; motion and tracking; document image analysis; big data, large scale methods.
Author: Christian Bentz Publisher: Walter de Gruyter GmbH & Co KG ISBN: 3110557770 Category : Language Arts & Disciplines Languages : en Pages : 223
Book Description
Languages carry information. To fulfil this purpose, they employ a multitude of coding strategies. This book explores a core property of linguistic coding – called lexical diversity. Parallel text corpora of overall more than 1800 texts written in more than 1200 languages are the basis for computational analyses. Different measures of lexical diversity are discussed and tested, and Shannon’s measure of uncertainty – the entropy – is chosen to assess differences in the distributions of words. To further explain this variation, a range of descriptive, explanatory, and grouping factors are considered in a series of statistical models. The first category includes writing systems, word-formation patterns, registers and styles. The second category includes population size, non-native speaker proportions and language status. Grouping factors further elicit whether the results extrapolate across – or are limited to – specific language families and areas. This account marries information-theoretic methods with a complex systems framework, illustrating how languages adapt to the varying needs of their users. It sheds light on the puzzling diversity of human languages in a quantitative, data driven and reproducible manner.
Author: Eduardo Reck Miranda Publisher: Springer Nature ISBN: 3030721167 Category : Computers Languages : en Pages : 994
Book Description
This book presents comprehensive coverage of the latest advances in research into enabling machines to listen to and compose new music. It includes chapters introducing what we know about human musical intelligence and on how this knowledge can be simulated with AI. The development of interactive musical robots and emerging new approaches to AI-based musical creativity are also introduced, including brain–computer music interfaces, bio-processors and quantum computing. Artificial Intelligence (AI) technology permeates the music industry, from management systems for recording studios to recommendation systems for online commercialization of music through the Internet. Yet whereas AI for online music distribution is well advanced, this book focuses on a largely unexplored application: AI for creating the actual musical content.
Author: Biao Luo Publisher: Springer Nature ISBN: 9819980739 Category : Computers Languages : en Pages : 621
Book Description
The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Author: Andreas K. Maier Publisher: Springer Nature ISBN: 3031476794 Category : Medical Languages : en Pages : 200
Book Description
This book constitutes the proceedings of the First International Workshop on Machine Learning for Multimodal Healthcare Date, ML4MHD 2023, held in Honolulu, Hawaii, USA, in July 2023. The 18 full papers presented were carefully reviewed and selected from 30 submissions. The workshop's primary objective was to bring together experts from diverse fields such as medicine, pathology, biology, and machine learning. With the aim to present novel methods and solutions that address healthcare challenges, especially those that arise from the complexity and heterogeneity of patient data.
Author: Jianwei Zhang
Author: Jianwei Zhang
Author: Manuel Diaz-Campos
Author: Stevan Rudinac
Author: Hayit Greenspan
Author: Yingmin Jia
Author: Lei Wang
Author: Christian Bentz
Author: Eduardo Reck Miranda
Author: Biao Luo
Author: Andreas K. Maier