no code implementations • 2 Mar 2024 • Jianan Fan, Dongnan Liu, Hang Chang, Heng Huang, Mei Chen, Weidong Cai
Machine learning holds tremendous promise for transforming the fundamental practice of scientific discovery by virtue of its data-driven nature.
no code implementations • 9 Feb 2024 • Yaxuan Song, Jianan Fan, Dongnan Liu, Weidong Cai
Source-free domain adaptation (SFDA) alleviates the domain discrepancy among data obtained from domains without accessing the data for the awareness of data privacy.
no code implementations • 17 Jan 2024 • Jianan Fan, Dongnan Liu, Hang Chang, Weidong Cai
Annotation scarcity and cross-modality/stain data distribution shifts are two major obstacles hindering the application of deep learning models for nuclei analysis, which holds a broad spectrum of potential applications in digital pathology.
1 code implementation • 14 Dec 2023 • Wenhai Wang, Jiangwei Xie, Chuanyang Hu, Haoming Zou, Jianan Fan, Wenwen Tong, Yang Wen, Silei Wu, Hanming Deng, Zhiqi Li, Hao Tian, Lewei Lu, Xizhou Zhu, Xiaogang Wang, Yu Qiao, Jifeng Dai
In this work, we delve into the potential of large language models (LLMs) in autonomous driving (AD).
1 code implementation • ICCV 2023 • Jianan Fan, Dongnan Liu, Hang Chang, Heng Huang, Mei Chen, Weidong Cai
The success of automated medical image analysis depends on large-scale and expert-annotated training sets.