no code implementations • 11 Feb 2024 • Xin Tong, Bo Jin, Zhi Lin, Binjun Wang, Ting Yu, Qiang Cheng
Large Language Models (LLMs) have demonstrated significant potential and effectiveness across multiple application domains.
no code implementations • 13 Jul 2023 • Nevin L. Zhang, Kaican Li, Han Gao, Weiyan Xie, Zhi Lin, Zhenguo Li, Luning Wang, Yongxiang Huang
Domain generalization (DG) is about learning models that generalize well to new domains that are related to, but different from, the training domain(s).
1 code implementation • 10 Jun 2023 • Weiyan Xie, Xiao-Hui Li, Zhi Lin, Leonard K. M. Poon, Caleb Chen Cao, Nevin L. Zhang
The need to explain the output of a deep neural network classifier is now widely recognized.
1 code implementation • 13 May 2023 • Han Gao, Kaican Li, Weiyan Xie, Zhi Lin, Yongxiang Huang, Luning Wang, Caleb Chen Cao, Nevin L. Zhang
In this paper, we consider a third, lesser-known setting where a training domain is endowed with a collection of pairs of examples that share the same semantic information.
2 code implementations • 1 Jul 2022 • Zhi Lin, Junhao Lin, Lei Zhu, Huazhu Fu, Jing Qin, Liansheng Wang
Moreover, we learn video-level features to classify the breast lesions of the original video as benign or malignant lesions to further enhance the final breast lesion detection performance in ultrasound videos.
1 code implementation • 16 Mar 2022 • Nevin L. Zhang, Weiyan Xie, Zhi Lin, Guanfang Dong, Xiao-Hui Li, Caleb Chen Cao, Yunpeng Wang
Some examples are easier for humans to classify than others.
no code implementations • 21 Apr 2016 • Xichuan Zhou, Shengli Li, Kai Qin, Kunping Li, Fang Tang, Shengdong Hu, Shujun Liu, Zhi Lin
Deep neural networks are state-of-the-art models for understanding the content of images, video and raw input data.