1 code implementation • 23 Mar 2024 • Jiacheng Ruan, Jingsheng Gao, Mingye Xie, Daize Dong, Suncheng Xiang, Ting Liu, Yuzhuo Fu
Adapter-Tuning (AT) method involves freezing a pre-trained model and introducing trainable adapter modules to acquire downstream knowledge, thereby calibrating the model for better adaptation to downstream tasks.
2 code implementations • 4 Feb 2024 • Jiacheng Ruan, Suncheng Xiang
To our best knowledge, this is the first medical image segmentation model constructed based on the pure SSM-based model.
no code implementations • 4 Jan 2024 • Zeyu Li, Jingsheng Gao, Tong Yu, Suncheng Xiang, Jiacheng Ruan, Ting Liu, Yuzhuo Fu
Existing research on audio classification faces challenges in recognizing attributes of passive underwater vessel scenarios and lacks well-annotated datasets due to data privacy concerns.
1 code implementation • 28 Dec 2023 • Jiacheng Ruan, Jingsheng Gao, Mingye Xie, Suncheng Xiang
Specifically, our block performs a Fourier transform on the three axes of the input features and assigns the external weight in the frequency domain, which is generated by our External Weights Generator.
1 code implementation • 13 Dec 2023 • Jingsheng Gao, Jiacheng Ruan, Suncheng Xiang, Zefang Yu, Ke Ji, Mingye Xie, Ting Liu, Yuzhuo Fu
We conduct experiments on 11 downstream vision datasets and demonstrate that our method significantly improves the performance of existing multi-modal prompt learning models in few-shot scenarios, exhibiting an average accuracy improvement of 2. 31(\%) compared to the state-of-the-art methods on 16 shots.
1 code implementation • 12 Dec 2023 • Jiacheng Ruan, Jingsheng Gao, Mingye Xie, Suncheng Xiang, Zefang Yu, Ting Liu, Yuzhuo Fu
2) They neglect the interaction between the intrinsic task-agnostic knowledge of pre-trained models and the task-specific knowledge in downstream tasks.
1 code implementation • 17 Jul 2023 • Jiacheng Ruan, Mingye Xie, Jingsheng Gao, Ting Liu, Yuzhuo Fu
Moreover, to our best knowledge, this is the first model with a parameter count limited to just 50KB.
1 code implementation • 19 Apr 2023 • Suncheng Xiang, Jingsheng Gao, Mengyuan Guan, Jiacheng Ruan, Chengfeng Zhou, Ting Liu, Dahong Qian, Yuzhuo Fu
In this paper, we propose a Multi-Modal Equivalent Transformer called MMET for more robust visual-semantic embedding learning on visual, textual and visual-textual tasks respectively.
Generalizable Person Re-identification Representation Learning
1 code implementation • 3 Nov 2022 • Jiacheng Ruan, Suncheng Xiang, Mingye Xie, Ting Liu, Yuzhuo Fu
To address this challenge, we propose a light-weight model to achieve competitive performances for skin lesion segmentation at the lowest cost of parameters and computational complexity so far.
1 code implementation • 25 Oct 2022 • Jiacheng Ruan, Mingye Xie, Suncheng Xiang, Ting Liu, Yuzhuo Fu
Specifically, our block performs a Fourier transform on the three axes of the input feature and assigns the external weight in the frequency domain, which is generated by our Weights Generator.
no code implementations • 14 Sep 2020 • Jiacheng Ruan, Jiahao Li
As a common method in Machine Learning, Ensemble Method is used to train multiple models from a data set and obtain better results through certain combination strategies.