Zobrazeno 1 - 10
of 345
pro vyhledávání: '"Li, Yunzhe"'
Autor:
Li, Yunzhe, Zhu, Hongzi, Deng, Zhuohong, Cheng, Yunlong, Zhang, Liang, Chang, Shan, Guo, Minyi
Emerging Artificial Intelligence of Things (AIoT) applications desire online prediction using deep neural network (DNN) models on mobile devices. However, due to the movement of devices, unfamiliar test samples constantly appear, significantly affect
Externí odkaz:
http://arxiv.org/abs/2407.03331
Autor:
Conde, Marcos V., Vasluianu, Florin-Alexandru, Timofte, Radu, Zhang, Jianxing, Li, Jia, Wang, Fan, Li, Xiaopeng, Liu, Zikun, Park, Hyunhee, Song, Sejun, Kim, Changho, Huang, Zhijuan, Yu, Hongyuan, Wan, Cheng, Xiang, Wending, Lin, Jiamin, Zhong, Hang, Zhang, Qiaosong, Sun, Yue, Yin, Xuanwu, Zuo, Kunlong, Xu, Senyan, Jiang, Siyuan, Sun, Zhijing, Zhu, Jiaying, Li, Liangyan, Chen, Ke, Li, Yunzhe, Ning, Yimo, Zhao, Guanhua, Chen, Jun, Yu, Jinyang, Xu, Kele, Xu, Qisheng, Dou, Yong
This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem
Externí odkaz:
http://arxiv.org/abs/2404.16223
Traditional fluorescence microscopy is constrained by inherent trade-offs among resolution, field-of-view, and system complexity. To navigate these challenges, we introduce a simple and low-cost computational multi-aperture miniature microscope, util
Externí odkaz:
http://arxiv.org/abs/2403.06439
Autor:
Yan, Weixiang, Liu, Haitian, Wang, Yunkun, Li, Yunzhe, Chen, Qian, Wang, Wen, Lin, Tingyu, Zhao, Weishan, Zhu, Li, Sundaram, Hari, Deng, Shuiguang
Large Language Models (LLMs) have demonstrated remarkable performance on assisting humans in programming and facilitating programming automation. However, existing benchmarks for evaluating the code understanding and generation capacities of LLMs suf
Externí odkaz:
http://arxiv.org/abs/2311.08588
Recent code translation techniques exploit neural machine translation models to translate source code from one programming language to another to satisfy production compatibility or to improve efficiency of codebase maintenance. Most existing code tr
Externí odkaz:
http://arxiv.org/abs/2310.04951
The Dynamic Zero-COVID Policy in China spanned three years and diverse emotional responses have been observed at different times. In this paper, we retrospectively analyzed public sentiments and perceptions of the policy, especially regarding how the
Externí odkaz:
http://arxiv.org/abs/2309.09324
Modern neural collaborative filtering techniques are critical to the success of e-commerce, social media, and content-sharing platforms. However, despite technical advances -- for every new application domain, we need to train an NCF model from scrat
Externí odkaz:
http://arxiv.org/abs/2309.01188
Optimization of methods for determining major triterpenoid compounds in Centella asiatica (L.) Urban
Publikováno v:
Xibei zhiwu xuebao, Vol 44, Iss 10, Pp 1639-1645 (2024)
Abstract [Objective] In order to provide a basis for quality control of Centella asiatica (L.) Urban, a high-performance liquid chromatography method was established using cyclodextrin as a mobile phase additive for the determination of asiaticosid
Externí odkaz:
https://doaj.org/article/7956dfee12b94d14a78584260b0910db
Autor:
Li, Yunzhe
Light scattering is a pervasive phenomenon that poses outstanding challenges in both coherent and incoherent imaging systems. The output of a coherent light scattered from a complex medium exhibits a seemingly random speckle pattern that scrambles th
Externí odkaz:
https://hdl.handle.net/2144/45463
Deep learning has transformed computational imaging, but traditional pixel-based representations limit their ability to capture continuous, multiscale details of objects. Here we introduce a novel Local Conditional Neural Fields (LCNF) framework, lev
Externí odkaz:
http://arxiv.org/abs/2307.06207