pubs2024

@inproceedings{Jesus2020549,

title = {Review of Trends in Automatic Human Activity Recognition Using Synthetic Audio-Visual Data},

author = {T. Jesus and J. Duarte and D. Ferreira and D. Durães and F. Marcondes and F. Santos and M. Gomes and P. Novais and F. Gonçalves and J. Fonseca and N. Lori and A. Abelha and J. Machado},

editor = {Camacho D. Novais P. Analide C.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097138094&doi=10.1007%2f978-3-030-62365-4_53&partnerID=40&md5=4f6f299f14229712acda0326b1718e1d},

doi = {10.1007/978-3-030-62365-4_53},

issn = {03029743},

year  = {2020},

date = {2020-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {12490 LNCS},

pages = {549-560},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {An in-depth study of knowledge and technologies was made related to the various scientific, technical, and industrial domains necessary for the acquisition of skills and capabilities for the design and development of a multisensory fusion system for vehicle cockpits. After an extensive literature review, it was possible to determine the baselines of the solution to be developed and obtain a pipeline prototype. © 2020, Springer Nature Switzerland AG.},

note = {cited By 4; Conference of 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020 ; Conference Date: 4 November 2020 Through 6 November 2020; Conference Code:251049},

keywords = {Artificial intelligence, Audio-visual data; Design and Development; Human activity recognition; In-depth study; Literature reviews; Multi-sensory fusion, Computer science; Computers},

pubstate = {published},

tppubtype = {inproceedings}

}