Zobrazeno 1 - 10
of 935
pro vyhledávání: '"Lo-An Chen"'
Autor:
Chia-Ying Lin, Hui-Ling Chang, Mong-Ting Wu, Yun-Zhan Cai, Yu-Ting Wang, Lo-An Chen, Meng-Hsun Tsai, Ren-Shiou Liu
Publikováno v:
IEEE Access, Vol 7, Pp 332-346 (2019)
Nowadays, Over-The-Top (OTT) voice call service has become more popular than other Voice over Internet Protocol services provided by mobile operators due to cheaper costs. For devices with more than one network interfaces, the OTT software may need t
Externí odkaz:
https://doaj.org/article/a4518824d7824bd2a9471f30effe2fca
Autor:
Tsao, Li-Yuan, Lo, Yi-Chen, Chang, Chia-Che, Chen, Hao-Wei, Tseng, Roy, Feng, Chien, Lee, Chun-Yi
Flow-based super-resolution (SR) models have demonstrated astonishing capabilities in generating high-quality images. However, these methods encounter several challenges during image generation, such as grid artifacts, exploding inverses, and subopti
Externí odkaz:
http://arxiv.org/abs/2403.10988
Flow-based methods have demonstrated promising results in addressing the ill-posed nature of super-resolution (SR) by learning the distribution of high-resolution (HR) images with the normalizing flow. However, these methods can only perform a predef
Externí odkaz:
http://arxiv.org/abs/2303.05156
Autor:
Chia-Ying Lin, Hui-Ling Chang, Mong-Ting Wu, Yun-Zhan Cai, Yu-Ting Wang, Lo-An Chen, Meng-Hsun Tsai, Ren-Shiou Liu
Publikováno v:
IEEE Access, Vol 7, Pp 175020-175020 (2019)
In the above paper [3], two references [1], [2]weremissing. The first sentence of Section III should read “This section proposes an analytical model for DHM, which is based on the mathematical analysis in [1] and [2]. Compared to [1] and [2], DHM h
Externí odkaz:
https://doaj.org/article/5d3a44d93b434a218d3e282e78917339
Autor:
Liao, Ting-Hsuan, Liao, Huang-Ru, Yang, Shan-Ya, Yao, Jie-En, Tsao, Li-Yuan, Liu, Hsu-Shen, Cheng, Bo-Wun, Chao, Chen-Hao, Chang, Chia-Che, Lo, Yi-Chen, Lee, Chun-Yi
Many unsupervised domain adaptation (UDA) methods have been proposed to bridge the domain gap by utilizing domain invariant information. Most approaches have chosen depth as such information and achieved remarkable success. Despite their effectivenes
Externí odkaz:
http://arxiv.org/abs/2211.08888
Autor:
Chao, Chen-Hao, Sun, Wei-Fang, Cheng, Bo-Wun, Lo, Yi-Chen, Chang, Chia-Che, Liu, Yu-Lun, Chang, Yu-Lin, Chen, Chia-Ping, Lee, Chun-Yi
Many existing conditional score-based data generation methods utilize Bayes' theorem to decompose the gradients of a log posterior density into a mixture of scores. These methods facilitate the training procedure of conditional score models, as a mix
Externí odkaz:
http://arxiv.org/abs/2203.14206
Autor:
Lo, Yi-Chen, Chang, Chia-Che, Chiu, Hsuan-Chao, Huang, Yu-Hao, Chen, Chia-Ping, Chang, Yu-Lin, Jou, Kevin
In this paper, we present CLCC, a novel contrastive learning framework for color constancy. Contrastive learning has been applied for learning high-quality visual representations for image classification. One key aspect to yield useful representation
Externí odkaz:
http://arxiv.org/abs/2106.04989
Publikováno v:
In Heliyon 30 January 2024 10(2)
Autor:
Bo-Rong Peng, Ngoc Bao An Nguyen, Lo-Yun Chen, Mohamed El-Shazly, Tsong-Long Hwang, Jui-Hsin Su, Kuei-Hung Lai
Publikováno v:
Aquaculture Reports, Vol 33, Iss , Pp 101835- (2023)
Recent advancements in the discovery of natural products have made significant progress in rapidly identifying known compounds from complex extracts using advanced spectroscopic technologies. Among these methods, one powerful approach called MS/MS mo
Externí odkaz:
https://doaj.org/article/d9416dd573f1420080e10a66c7841ed6
This paper aims to tackle the challenging problem of one-shot object detection. Given a query image patch whose class label is not included in the training data, the goal of the task is to detect all instances of the same class in a target image. To
Externí odkaz:
http://arxiv.org/abs/1911.12529