Conference Paper/Proceeding/Abstract 108 views 6 downloads
Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
Bahareh Nakisa,
Sara Sardari,
Sara Sharifzadeh
,
Alireza Daneshkhah,
Seng W. Loke,
Vasile Palade,
Michael J. Duncan,
Matteo Crotti
Volume: IEEE Consumer life Tech Conference
Swansea University Author:
Sara Sharifzadeh
-
PDF | Accepted Manuscript
Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention).
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Abstract
Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
Published: |
IEEE
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URI: | https://cronfa.swan.ac.uk/Record/cronfa68670 |
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2025-01-10T20:24:20Z |
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last_indexed |
2025-03-20T08:09:40Z |
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2025-03-19T15:41:37.9596204 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 IEEE Consumer life Tech Conference IEEE 0 0 0 0001-01-01 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 2025-03-19T15:41:37.9596204 2025-01-10T12:05:55.3017593 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Bahareh Nakisa 1 Sara Sardari 2 Sara Sharifzadeh 0000-0003-4621-2917 3 Alireza Daneshkhah 4 Seng W. Loke 5 Vasile Palade 6 Michael J. Duncan 7 Matteo Crotti 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 |
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a4e15f304398ecee3f28c7faec69c1b0 |
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a4e15f304398ecee3f28c7faec69c1b0_***_Sara Sharifzadeh |
author |
Sara Sharifzadeh |
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Bahareh Nakisa Sara Sardari Sara Sharifzadeh Alireza Daneshkhah Seng W. Loke Vasile Palade Michael J. Duncan Matteo Crotti |
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School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science |
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0001-01-01T08:18:30Z |
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11.055092 |