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Conference Paper/Proceeding/Abstract 406 views 81 downloads

Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention

Sara Sardari, Bahareh Nakisa, Sara Sharifzadeh Orcid Logo, Alireza Daneshkhah, Seng W. Loke, Michael J. Duncan, Matteo Crotti, Vasile Palade

2024 IEEE Consumer Life Tech (ICLT), Pages: 1 - 6

Swansea University Author: Sara Sharifzadeh Orcid Logo

  • meta_learning_conference_final.pdf

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DOI (Published version): 10.1109/iclt63507.2024.11038644

Published in: 2024 IEEE Consumer Life Tech (ICLT)
ISBN: 979-8-3315-1934-6 979-8-3315-1933-9
Published: IEEE 2025
URI: https://cronfa.swan.ac.uk/Record/cronfa68670
first_indexed 2025-01-10T20:24:20Z
last_indexed 2025-07-01T05:24:18Z
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spelling 2025-06-30T12:11:16.3185608 v2 68670 2025-01-10 Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention a4e15f304398ecee3f28c7faec69c1b0 0000-0003-4621-2917 Sara Sharifzadeh Sara Sharifzadeh true false 2025-01-10 MACS Conference Paper/Proceeding/Abstract 2024 IEEE Consumer Life Tech (ICLT) 1 6 IEEE 979-8-3315-1934-6 979-8-3315-1933-9 Metalearning, Continuing education, Adaptation models, Three-dimensional displays, Frequency modulation, Skeleton, Sensors, Quality assessment, Monitoring, Videos 19 6 2025 2025-06-19 10.1109/iclt63507.2024.11038644 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Not Required Co tutelle PhD funded between Coventry University and Deakin University, Australia 2025-06-30T12:11:16.3185608 2025-01-10T12:05:55.3017593 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Sara Sardari 1 Bahareh Nakisa 2 Sara Sharifzadeh 0000-0003-4621-2917 3 Alireza Daneshkhah 4 Seng W. Loke 5 Michael J. Duncan 6 Matteo Crotti 7 Vasile Palade 8 68670__33740__7f0e7f5b9a3346afa512834ec7463d7c.pdf meta_learning_conference_final.pdf 2025-03-06T11:15:19.0661850 Output 613244 application/pdf Accepted Manuscript true Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention). true eng https://creativecommons.org/licenses/by/4.0/deed.en
title Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
spellingShingle Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
Sara Sharifzadeh
title_short Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
title_full Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
title_fullStr Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
title_full_unstemmed Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
title_sort Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
author_id_str_mv a4e15f304398ecee3f28c7faec69c1b0
author_id_fullname_str_mv a4e15f304398ecee3f28c7faec69c1b0_***_Sara Sharifzadeh
author Sara Sharifzadeh
author2 Sara Sardari
Bahareh Nakisa
Sara Sharifzadeh
Alireza Daneshkhah
Seng W. Loke
Michael J. Duncan
Matteo Crotti
Vasile Palade
format Conference Paper/Proceeding/Abstract
container_title 2024 IEEE Consumer Life Tech (ICLT)
container_start_page 1
publishDate 2025
institution Swansea University
isbn 979-8-3315-1934-6
979-8-3315-1933-9
doi_str_mv 10.1109/iclt63507.2024.11038644
publisher IEEE
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
published_date 2025-06-19T05:21:54Z
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score 11.089988

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