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Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model

AALAA HUMAIDAN, Jeny Roy Orcid Logo, Sara Sharifzadeh Orcid Logo, Ruchita Mehta, Andrea Tales Orcid Logo, Joe MacInnes Orcid Logo

2025 IEEE Symposium on Computational Intelligence in Image, Signal Processing and Synthetic Media Companion (CISM Companion), Pages: 1 - 5

Swansea University Authors: AALAA HUMAIDAN, Jeny Roy Orcid Logo, Sara Sharifzadeh Orcid Logo, Andrea Tales Orcid Logo, Joe MacInnes Orcid Logo

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DOI (Published version): 10.1109/cismcompanion65074.2025.11032695

Published in: 2025 IEEE Symposium on Computational Intelligence in Image, Signal Processing and Synthetic Media Companion (CISM Companion)
ISBN: 979-8-3315-0852-4 979-8-3315-0851-7
Published: IEEE 2025
URI: https://cronfa.swan.ac.uk/Record/cronfa69135
first_indexed 2025-03-22T16:01:52Z
last_indexed 2025-06-28T07:52:30Z
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spelling 2025-06-27T12:28:38.8498359 v2 69135 2025-03-22 Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model 9d418b788707447f2ad49125fa3867cf AALAA HUMAIDAN AALAA HUMAIDAN true false 00fd1a17e776f2e1d532ab4125995465 0009-0006-3354-7557 Jeny Roy Jeny Roy true false a4e15f304398ecee3f28c7faec69c1b0 0000-0003-4621-2917 Sara Sharifzadeh Sara Sharifzadeh true false 9b53a866ddacb566c38ee336706aef5f 0000-0003-4825-4555 Andrea Tales Andrea Tales true false 06dcb003ec50192bafde2c77bef4fd5c 0000-0002-5134-1601 Joe MacInnes Joe MacInnes true false 2025-03-22 MACS Conference Paper/Proceeding/Abstract 2025 IEEE Symposium on Computational Intelligence in Image, Signal Processing and Synthetic Media Companion (CISM Companion) 1 5 IEEE 979-8-3315-0852-4 979-8-3315-0851-7 Accuracy, Computational modeling, Noise, Pipelines, Transformers, Feature extraction, Data models, Acoustics, Human activity recognition, Convolutional neural networks 17 6 2025 2025-06-17 10.1109/cismcompanion65074.2025.11032695 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Not Required This project is partly supported by Swansea University IAA funding scheme and Coventry University 2025-06-27T12:28:38.8498359 2025-03-22T11:51:08.4451291 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science AALAA HUMAIDAN 1 Jeny Roy 0009-0006-3354-7557 2 Sara Sharifzadeh 0000-0003-4621-2917 3 Ruchita Mehta 4 Andrea Tales 0000-0003-4825-4555 5 Joe MacInnes 0000-0002-5134-1601 6 69135__33859__8b03d12386bc415886fd571aded0b2ac.pdf IEEE_Conference_Template_Revised_Submission.pdf 2025-03-22T13:13:21.7234283 Output 318034 application/pdf Accepted Manuscript true 2025-04-22T00:00:00.0000000 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 Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model
spellingShingle Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model
AALAA HUMAIDAN
Jeny Roy
Sara Sharifzadeh
Andrea Tales
Joe MacInnes
title_short Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model
title_full Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model
title_fullStr Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model
title_full_unstemmed Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model
title_sort Exploring Human Activity Recognition with Acoustic Data: A Comparative Study of CNN-LSTM, ViViT, and ResNet-Temporal Transformer Model
author_id_str_mv 9d418b788707447f2ad49125fa3867cf
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author_id_fullname_str_mv 9d418b788707447f2ad49125fa3867cf_***_AALAA HUMAIDAN
00fd1a17e776f2e1d532ab4125995465_***_Jeny Roy
a4e15f304398ecee3f28c7faec69c1b0_***_Sara Sharifzadeh
9b53a866ddacb566c38ee336706aef5f_***_Andrea Tales
06dcb003ec50192bafde2c77bef4fd5c_***_Joe MacInnes
author AALAA HUMAIDAN
Jeny Roy
Sara Sharifzadeh
Andrea Tales
Joe MacInnes
author2 AALAA HUMAIDAN
Jeny Roy
Sara Sharifzadeh
Ruchita Mehta
Andrea Tales
Joe MacInnes
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container_title 2025 IEEE Symposium on Computational Intelligence in Image, Signal Processing and Synthetic Media Companion (CISM Companion)
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institution Swansea University
isbn 979-8-3315-0852-4
979-8-3315-0851-7
doi_str_mv 10.1109/cismcompanion65074.2025.11032695
publisher IEEE
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published_date 2025-06-17T05:26:09Z
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