Zobrazeno 1 - 10
of 10 271
pro vyhledávání: '"Lee, Chun"'
The stability of the integrated photonic circuits is of critical importance for many applications that require high frequency precision or robust operation over time, such as optomechanical sensing, frequency conversion, optical communication, and qu
Externí odkaz:
http://arxiv.org/abs/2409.12354
In this paper, we propose a novel coarse-to-fine continuous pose diffusion method to enhance the precision of pick-and-place operations within robotic manipulation tasks. Leveraging the capabilities of diffusion networks, we facilitate the accurate p
Externí odkaz:
http://arxiv.org/abs/2409.09725
Autor:
Liu, Ting-Ru, Yang, Hsuan-Kung, Liu, Jou-Min, Huang, Chun-Wei, Chiang, Tsung-Chih, Kong, Quan, Kobori, Norimasa, Lee, Chun-Yi
Scene coordinate regression (SCR) methods have emerged as a promising area of research due to their potential for accurate visual localization. However, many existing SCR approaches train on samples from all image regions, including dynamic objects a
Externí odkaz:
http://arxiv.org/abs/2409.04178
Autor:
Chuang, Yao-Shun, Lee, Chun-Teh, Tokede, Oluwabunmi, Lin, Guo-Hao, Brandon, Ryan, Tran, Trung Duong, Jiang, Xiaoqian, Walji, Muhammad F.
This research addresses the issue of missing structured data in dental records by extracting diagnostic information from unstructured text. The updated periodontology classification system's complexity has increased incomplete or missing structured d
Externí odkaz:
http://arxiv.org/abs/2407.21050
Existing Maximum-Entropy (MaxEnt) Reinforcement Learning (RL) methods for continuous action spaces are typically formulated based on actor-critic frameworks and optimized through alternating steps of policy evaluation and policy improvement. In the p
Externí odkaz:
http://arxiv.org/abs/2405.13629
Autor:
Chen, Hao-Wei, Xu, Yu-Syuan, Chan, Kelvin C. K., Kuo, Hsien-Kai, Lee, Chun-Yi, Yang, Ming-Hsuan
Existing image restoration approaches typically employ extensive networks specifically trained for designated degradations. Despite being effective, such methods inevitably entail considerable storage costs and computational overheads due to the reli
Externí odkaz:
http://arxiv.org/abs/2404.11475
Autor:
Shen, Mu-Yi, Hsu, Chia-Chi, Hou, Hao-Yu, Huang, Yu-Chen, Sun, Wei-Fang, Chang, Chia-Che, Liu, Yu-Lun, Lee, Chun-Yi
In this study, we introduce the DriveEnv-NeRF framework, which leverages Neural Radiance Fields (NeRF) to enable the validation and faithful forecasting of the efficacy of autonomous driving agents in a targeted real-world scene. Standard simulator-b
Externí odkaz:
http://arxiv.org/abs/2403.15791
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
Autor:
Lam, Leo S. I., Gopinath, Gautham, Zhao, Zichen, Wang, Shuling, Lee, Chun-Shing, Deng, Hai-Yao, Wang, Feng, Han, Yilong, Yip, Cho-Tung, Lam, Chi-Hang
The nature of glassy dynamics and the glass transition are long-standing problems under active debate. In the presence of a structural disorder widely believed to be an essential characteristic of structural glass, identifying and understanding key d
Externí odkaz:
http://arxiv.org/abs/2402.15805