no code implementations • 3 May 2024 • Siqi Yin, Lifan Jiang
Specifically, we propose three strategies to enhance the model's performance to handle ZSL: 1) Utilizing the extensive knowledge of ChatGPT and the powerful image generation capabilities of DALL-E to create reference images that can precisely describe unseen categories and classification boundaries, thereby alleviating the information bottleneck issue; 2) Integrating the results of text-image alignment and image-image alignment from CLIP, along with the image-image alignment results from DINO, to achieve more accurate predictions; 3) Introducing an adaptive weighting mechanism based on confidence levels to aggregate the outcomes from different prediction methods.
no code implementations • 28 Nov 2022 • Shaolei Liu, Siqi Yin, Linhao Qu, Manning Wang
Unsupervised domain adaptation (UDA) aims to learn a model trained on source domain and performs well on unlabeled target domain.
no code implementations • 19 Jan 2022 • Linhao Qu, Shaolei Liu, Manning Wang, Shiman Li, Siqi Yin, Qin Qiao, Zhijian Song
In order to encourage different fusion tasks to promote each other and increase the generalizability of the trained network, we integrate the three self-supervised auxiliary tasks by randomly choosing one of them to destroy a natural image in model training.
no code implementations • 21 Jan 2021 • Yongjian Zhou, Liyang Liao, Xiaofeng Zhou, Hua Bai, Mingkun Zhao, Caihua Wan, Siqi Yin, Lin Huang, Tingwen Guo, Lei Han, Ruyi Chen, Zhiyuan Zhou, Xiufeng Han, Feng Pan, Cheng Song
The interlayer coupling mediated by fermions in ferromagnets brings about parallel and anti-parallel magnetization orientations of two magnetic layers, resulting in the giant magnetoresistance, which forms the foundation in spintronics and accelerates the development of information technology.
Materials Science