Zobrazeno 1 - 10
of 805
pro vyhledávání: '"GUO Weidong"'
Publikováno v:
Redai dili, Vol 43, Iss 4, Pp 596-607 (2023)
Urban creative networks, as distinct forms of production networks, differ from inter-firm-based urban networks. It is featured by flexible production, "temporary cooperation" and being "people-centered." This study attempts to address the concept of
Externí odkaz:
https://doaj.org/article/a5fb035ea31d4d86b8d5adbcfc792939
Accurate segmentation of rectal lymph nodes is crucial for the staging and treatment planning of rectal cancer. However, the complexity of the surrounding anatomical structures and the scarcity of annotated data pose significant challenges. This stud
Externí odkaz:
http://arxiv.org/abs/2408.14977
The effective alignment of Large Language Models (LLMs) with precise instructions is essential for their application in diverse real-world scenarios. Current methods focus on enhancing the diversity and complexity of training and evaluation samples,
Externí odkaz:
http://arxiv.org/abs/2406.11301
Publikováno v:
Gong-kuang zidonghua, Vol 46, Iss 10, Pp 69-75 (2020)
In order to optimize control of energy saving, the key to coal transportation system is real-time detection of coal flow of belt conveyor and frequency conversion speed regulation control according to coal flow. At present, most of mine belt conveyor
Externí odkaz:
https://doaj.org/article/53ca7c9cfa1f4d65b2369cbadbf0a4f8
Publikováno v:
Gong-kuang zidonghua, Vol 45, Iss 11, Pp 81-85 (2019)
The multi-scale Retinex algorithm has some problems such as insufficient detail enhancement and long time-consumption in processing low-illumination image of underground coal mine. Aiming at the problem, a fast multi-scale Retinex algorithm based on
Externí odkaz:
https://doaj.org/article/be160d5c17a644bf983d38aa3d03779d
Autor:
Guo, Weidong, Zhang, Hantao, Wan, Shouhong, Zou, Bingbing, Wang, Wanqin, Qiu, Chenyang, Li, Jun, Jin, Peiquan
Accurate segmentation of metastatic lymph nodes in rectal cancer is crucial for the staging and treatment of rectal cancer. However, existing segmentation approaches face challenges due to the absence of pixel-level annotated datasets tailored for ly
Externí odkaz:
http://arxiv.org/abs/2404.08916
Autor:
Li, Ang, Xiao, Qiugen, Cao, Peng, Tang, Jian, Yuan, Yi, Zhao, Zijie, Chen, Xiaoyuan, Zhang, Liang, Li, Xiangyang, Yang, Kaitong, Guo, Weidong, Gan, Yukang, Yu, Xu, Wang, Daniell, Shan, Ying
Reinforcement Learning from AI Feedback (RLAIF) has the advantages of shorter annotation cycles and lower costs over Reinforcement Learning from Human Feedback (RLHF), making it highly efficient during the rapid strategy iteration periods of large la
Externí odkaz:
http://arxiv.org/abs/2403.08309
Ensuring factual consistency between the summary and the original document is paramount in summarization tasks. Consequently, considerable effort has been dedicated to detecting inconsistencies. With the advent of Large Language Models (LLMs), recent
Externí odkaz:
http://arxiv.org/abs/2403.07557
Autor:
Qi, Lu, Chen, Yi-Wen, Yang, Lehan, Shen, Tiancheng, Li, Xiangtai, Guo, Weidong, Xu, Yu, Yang, Ming-Hsuan
In this work, we propose a novel approach to densely ground visual entities from a long caption. We leverage a large multimodal model (LMM) to extract semantic nouns, a class-agnostic segmentation model to generate entity-level segmentation, and the
Externí odkaz:
http://arxiv.org/abs/2402.02555
The fine-tuning of Large Language Models (LLMs) specialized in code generation has seen notable advancements through the use of open-domain coding queries. Despite the successes, existing methodologies like Evol-Instruct encounter performance limitat
Externí odkaz:
http://arxiv.org/abs/2312.15692