Summary of the 2024 Low-Power Efficient and Accurate Facial-Landmark Detection for Embedded Systems-Reference-Cited by-同舟云学术

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Summary of the 2024 Low-Power Efficient and Accurate Facial-Landmark Detection for Embedded Systems

Published:2024-07-15 Issue: Volume:964 Page:1-6
ISSN:
Container-title:2024 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)
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Author:

Ni Yu-Shu¹,Chen Han-Chun¹,Tsai Chia-Chi²,Chen Chih-Cheng³,Chen Po-Yu³,Kuo Hsien-Kai¹,Hunag Jun-Ying¹,Hu Po-Chi⁴,Hwang Jenq-Neng⁵,Guo Jiun-In¹

Affiliation:

1. National Yang Ming Chiao Tung University,Department of Electronics Engineering and Institute of Electronics,Taiwan

2. National Cheng Kung University,Department of Electrical Engineering,Taiwan

3. MediaTek Inc.,Taiwan

4. Pervasive Artificial Intelligence Research Labs (PAIR Labs),Hsinchu,Taiwan

5. University of Washington,Department of Electrical Engineering,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10645349/10645352/10645442.pdf?arnumber=10645442

Reference17 articles.

1. Summary Embedded Deep Learning Object Detection Model Competition

2. The 2020 Embedded Deep Learning Object Detection Model Compression Competition for Traffic in Asian Countries

3. Summary of the 2021 Embedded Deep Learning Object Detection Model Compression Competition for Traffic in Asian Countries

4. Summary of the 2022 Low-Power Deep Learning Semantic Segmentation Model Compression Competition for Traffic Scene In Asian Countries

5. Summary of the 2023 Low-Power Deep Learning Object Detection and Semantic Segmentation Multitask Model Compression Competition for Traffic Scene in Asian Countries

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