Zobrazeno 1 - 10
of 258
pro vyhledávání: '"Chang, Chih-Peng"'
Autor:
Ho, Yung-Han, Lin, Chih-Hsuan, Chen, Peng-Yu, Chen, Mu-Jung, Chang, Chih-Peng, Peng, Wen-Hsiao, Hang, Hsueh-Ming
This paper proposes a learning-based video compression framework for variable-rate coding on YUV 4:2:0 content. Most existing learning-based video compression models adopt the traditional hybrid-based coding architecture, which involves temporal pred
Externí odkaz:
http://arxiv.org/abs/2210.08225
This paper presents an end-to-end learning-based video compression system, termed CANF-VC, based on conditional augmented normalizing flows (CANF). Most learned video compression systems adopt the same hybrid-based coding architecture as the traditio
Externí odkaz:
http://arxiv.org/abs/2207.05315
Autor:
Su, Pei-Chia, Chen, Ching-Yu, Yu, Min-Hua, Kuo, I.-Ying, Yang, Pei-Shan, Hsu, Ching-Hsuan, Hou, Ya-Chin, Hsieh, Hsin-Ta, Chang, Chih-Peng, Shan, Yan-Shen, Wang, Yi-Ching
Publikováno v:
In Biomedicine & Pharmacotherapy July 2024 176
Autor:
Lin, Yu-Jheng, Wang, Li-Chiu, Tsai, Huey-Pin, Chi, Chia-Yu, Chang, Chih-Peng, Chen, Shun-Hua, Wang, Shih-Min
Publikováno v:
In Virus Research 15 October 2023 336
Akademický článek
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Autor:
CHANG, CHIH-PENG, 張志鵬
106
This study aimed to improve the trap efficiency by light source selection and enhancing light efficiency of the insect trap lamp. Meanwhile, the lamp was then incorporated into decoration of the restaurant to improve and maintain environment
This study aimed to improve the trap efficiency by light source selection and enhancing light efficiency of the insect trap lamp. Meanwhile, the lamp was then incorporated into decoration of the restaurant to improve and maintain environment
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/hf79kc
This paper introduces the notion of soft bits to address the rate-distortion optimization for learning-based image compression. Recent methods for such compression train an autoencoder end-to-end with an objective to strike a balance between distorti
Externí odkaz:
http://arxiv.org/abs/1905.00190
We propose a lossy image compression system using the deep-learning autoencoder structure to participate in the Challenge on Learned Image Compression (CLIC) 2018. Our autoencoder uses the residual blocks with skip connections to reduce the correlati
Externí odkaz:
http://arxiv.org/abs/1902.07385
Autor:
Yang, You-En, Hu, Meng-Hsuan, Zeng, Yen-Chen, Tseng, Yau-Lin, Chen, Ying-Yung, Su, Wu-Chou, Chang, Chih-Peng, Wang, Yi-Ching
Publikováno v:
Cell Death & Disease; May2024, Vol. 15 Issue 5, p1-13, 13p
Akademický článek
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