Intra-class variations with deep learning-based gait analysis: A comprehensive survey of covariates and methods

Anubha Parashar; Rajveer Singh Shekhawat; Weiping Ding; Imad Rida

doi:10.1016/j.neucom.2022.07.002

Journal Articles Neurocomputing Year : 2022

Intra-class variations with deep learning-based gait analysis: A comprehensive survey of covariates and methods

(1) , (1) , (2) , (3)

1
2
3

Anubha Parashar

Function : Author

School of Computer Science and Engineering, Manipal University Jaipur

Rajveer Singh Shekhawat

Function : Author

School of Computer Science and Engineering, Manipal University Jaipur

Weiping Ding

Function : Author

School of Information Science and Technology, Nantong University

Imad Rida

Function : Author

Biomécanique et Bioingénierie

Domains

Computer Science [cs]

Imad Rida : Connect in order to contact the contributor

https://hal.utc.fr/hal-04236482

Submitted on : Tuesday, October 10, 2023-11:07:47 PM

Last modification on : Wednesday, October 11, 2023-3:38:01 AM

Dates and versions

hal-04236482 , version 1 (10-10-2023)

Identifiers

HAL Id : hal-04236482 , version 1
DOI : 10.1016/j.neucom.2022.07.002

Cite

Anubha Parashar, Rajveer Singh Shekhawat, Weiping Ding, Imad Rida. Intra-class variations with deep learning-based gait analysis: A comprehensive survey of covariates and methods. Neurocomputing, 2022, 505, pp.315-338. ⟨10.1016/j.neucom.2022.07.002⟩. ⟨hal-04236482⟩

Export

BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite

Collections

CNRS UNIV-COMPIEGNE BMBI

20 View

0 Download

Intra-class variations with deep learning-based gait analysis: A comprehensive survey of covariates and methods

Domains

Dates and versions

Identifiers

Cite

Export

Collections

Altmetric

Share