Zobrazeno 1 - 10
of 7 516
pro vyhledávání: '"FANG, Hui"'
Autor:
Yang, Guofeng, Li, Yu, He, Yong, Zhou, Zhenjiang, Ye, Lingzhen, Fang, Hui, Luo, Yiqi, Feng, Xuping
UAV remote sensing technology has become a key technology in crop breeding, which can achieve high-throughput and non-destructive collection of crop phenotyping data. However, the multidisciplinary nature of breeding has brought technical barriers an
Externí odkaz:
http://arxiv.org/abs/2411.15203
The widespread use of the internet has led to an overwhelming amount of data, which has resulted in the problem of information overload. Recommender systems have emerged as a solution to this problem by providing personalized recommendations to users
Externí odkaz:
http://arxiv.org/abs/2408.07630
Autor:
Yang, Xin, Lu, Xuqi, Xie, Pengyao, Guo, Ziyue, Fang, Hui, Fu, Haowei, Hu, Xiaochun, Sun, Zhenbiao, Cen, Haiyan
The rice panicle traits significantly influence grain yield, making them a primary target for rice phenotyping studies. However, most existing techniques are limited to controlled indoor environments and difficult to capture the rice panicle traits u
Externí odkaz:
http://arxiv.org/abs/2408.02053
Conversational recommender system (CRS), which combines the techniques of dialogue system and recommender system, has obtained increasing interest recently. In contrast to traditional recommender system, it learns the user preference better through i
Externí odkaz:
http://arxiv.org/abs/2408.01342
Publikováno v:
NLDB2024
With the increasing research attention on fairness in information retrieval systems, more and more fairness-aware algorithms have been proposed to ensure fairness for a sustainable and healthy retrieval ecosystem. However, as the most adopted measure
Externí odkaz:
http://arxiv.org/abs/2407.08926
Autor:
Chen, Fumian, Fang, Hui
Ranking algorithms as an essential component of retrieval systems have been constantly improved in previous studies, especially regarding relevance-based utilities. In recent years, more and more research attempts have been proposed regarding fairnes
Externí odkaz:
http://arxiv.org/abs/2405.17798
Large Language Models (LLMs) have demonstrated great potential in Conversational Recommender Systems (CRS). However, the application of LLMs to CRS has exposed a notable discrepancy in behavior between LLM-based CRS and human recommenders: LLMs often
Externí odkaz:
http://arxiv.org/abs/2404.11773
Session-based recommender systems (SBRSs) have become extremely popular in view of the core capability of capturing short-term and dynamic user preferences. However, most SBRSs primarily maximize recommendation accuracy but ignore user minor preferen
Externí odkaz:
http://arxiv.org/abs/2404.00261
Autor:
Jing, Linglin, Ding, Yiming, Gao, Yunpeng, Wang, Zhigang, Yan, Xu, Wang, Dong, Schaefer, Gerald, Fang, Hui, Zhao, Bin, Li, Xuelong
Event-based semantic segmentation has gained popularity due to its capability to deal with scenarios under high-speed motion and extreme lighting conditions, which cannot be addressed by conventional RGB cameras. Since it is hard to annotate event da
Externí odkaz:
http://arxiv.org/abs/2403.16788