HPFL: Federated Learning by Fusing Multiple Sensor Modalities with Heterogeneous Privacy Sensitivity Levels-Reference-Cited by-同舟云学术

HPFL: Federated Learning by Fusing Multiple Sensor Modalities with Heterogeneous Privacy Sensitivity Levels

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 1st International Workshop on Methodologies for Multimedia
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Author:

Chen Yuanjie¹,Hsu Chih-Fan²,Tsai Chung-Chi³,Hsu Cheng-Hsin¹

Affiliation:

1. National Tsing Hua University, Hsin-Chu, Taiwan Roc

2. National Yang Ming Chiao Tung University, Hsin-Chu, Taiwan Roc

3. Qualcomm Technologies, Inc., San Diego, CA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3552487.3556438

Reference73 articles.

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2. An audiovisual and contextual approach for categorical and continuous emotion recognition in-the-wild

3. Multimodal machine learning: A survey and taxonomy;Baltrusaitis Tadas;IEEE Transactions on Pattern Analysis and Machine Intelligence,2018

4. Decentralised Learning in Federated Deployment Environments

5. IEMOCAP: interactive emotional dyadic motion capture database

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1. Federated Learning Using Multi-Modal Sensors with Heterogeneous Privacy Sensitivity Levels;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-08-05

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