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Cross-Modal Learning: Adaptivity, Prediction and Interaction

Cross-Modal Learning: Adaptivity, Prediction and Interaction PDF 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.

Cross-Modal Learning: Adaptivity, Prediction and Interaction

Cross-Modal Learning: Adaptivity, Prediction and Interaction PDF 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.

The Handbook of Usage-Based Linguistics

The Handbook of Usage-Based Linguistics PDF 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.

MultiMedia Modeling

MultiMedia Modeling PDF Author: Stevan Rudinac
Publisher: Springer Nature
ISBN: 3031533119
Category :
Languages : en
Pages : 552

Book Description


Artificial Neural Networks and Machine Learning – ICANN 2023

Artificial Neural Networks and Machine Learning – ICANN 2023 PDF Author: Lazaros Iliadis
Publisher: Springer Nature
ISBN: 3031442105
Category : Computers
Languages : en
Pages : 626

Book Description
The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023. The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.

Body Representations, Peripersonal Space, and the Self: Humans, Animals, Robots

Body Representations, Peripersonal Space, and the Self: Humans, Animals, Robots PDF Author: Matej Hoffmann
Publisher: Frontiers Media SA
ISBN: 2889638774
Category :
Languages : en
Pages : 242

Book Description


Database Systems for Advanced Applications

Database Systems for Advanced Applications PDF Author: Christian S. Jensen
Publisher: Springer Nature
ISBN: 3030731979
Category : Computers
Languages : en
Pages : 801

Book Description
The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.

Computer Vision – ACCV 2022

Computer Vision – ACCV 2022 PDF Author: Lei Wang
Publisher: Springer Nature
ISBN: 3031263162
Category : Computers
Languages : en
Pages : 781

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.

Machine Learning Methods for High-Level Cognitive Capabilities in Robotics

Machine Learning Methods for High-Level Cognitive Capabilities in Robotics PDF Author: Emre Ugur
Publisher: Frontiers Media SA
ISBN: 288963261X
Category :
Languages : en
Pages : 149

Book Description


Image and Graphics

Image and Graphics PDF Author: Huchuan Lu
Publisher: Springer Nature
ISBN: 3031463056
Category : Computers
Languages : en
Pages : 456

Book Description
The five-volume set LNCS 14355, 14356, 14357, 14358 and 14359 constitutes the refereed proceedings of the 12th International Conference on Image and Graphics, ICIG 2023, held in Nanjing, China, during September 22–24, 2023. The 166 papers presented in the proceedings set were carefully reviewed and selected from 409 submissions. They were organized in topical sections as follows: computer vision and pattern recognition; computer graphics and visualization; compression, transmission, retrieval; artificial intelligence; biological and medical image processing; color and multispectral processing; computational imaging; multi-view and stereoscopic processing; multimedia security; surveillance and remote sensing, and virtual reality. The ICIG 2023 is a biennial conference that focuses on innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking. It will feature world-class plenary speakers, exhibits, and high-quality peer reviewed oral and poster presentations.

Re-Enacting Sensorimotor Experience for Cognition

Re-Enacting Sensorimotor Experience for Cognition PDF Author: Guido Schillaci
Publisher: Frontiers Media SA
ISBN: 2889451488
Category :
Languages : en
Pages : 165

Book Description
Mastering the sensorimotor capabilities of our body is a skill that we acquire and refine over time, starting at the prenatal stages of development. This learning process is linked to brain development and is shaped by the rich set of multimodal information experienced while exploring and interacting with the environment. Evidence coming from neuroscience suggests the brain forms and mantains body representations as the main strategy to this mastering. Although it is still not clear how this knowledge is represented in our brain, it is reasonable to think that such internal models of the body undergo a continuous process of adaptation. They need to match growing corporal dimensions during development, as well as temporary changes in the characteristics of the body, such as the transient morphological alterations produced by the usage of tools. In the robotics community there is an increasing interest in reproducing similar mechanisms in artificial agents, mainly motivated by the aim of producing autonomous adaptive systems that can deal with complexity and uncertainty in human environments. Although promising results have been achieved in the context of sensorimotor learning and autonomous generation of body representations, it is still not clear how such low-level representations can be scaled up to more complex motor skills and how they can enable the development of cognitive capabilities. Recent findings from behavioural and brain studies suggests that processes of mental simulations of action-perception loops are likely to be executed in our brain and are dependent on internal motor representations. The capability to simulate sensorimotor experience might represent a key mechanism behind the implementation of further cognitive skills, such as self-detection, self-other distinction and imitation. Empirical investigation on the functioning of similar processes in the brain and on their implementation in artificial agents is fragmented. This e-book comprises a collection of manuscripts published by Frontiers in Robotics and Artificial Intelligence, under the section Humanoid Robotics, on the research topic re-enactment of sensorimotor experience for cognition in artificial agents. This compendium aims at condensing the latest theoretical, review and experimental studies that address new paradigms for learning and integrating multimodal sensorimotor information in artificial agents, re-use of the sensorimotor experience for cognitive development and further construction of more complex strategies and behaviours using these concepts. The authors would like to thank M.A. Dylan Andrade for his art work for the cover.