no code implementations • 10 Apr 2024 • Zhenxi Zhang, Heng Zhou, Xiaoran Shi, Ran Ran, Chunna Tian, Feng Zhou
Additionally, the evidential fusion branch capitalizes on the complementary attributes of the first two branches and leverages an evidence-based Dempster-Shafer fusion strategy, supervised by more reliable and accurate pseudo-labels of unlabeled data.
no code implementations • 14 Jul 2023 • ShangQi Deng, RuoCheng Wu, Liang-Jian Deng, Ran Ran, Gemine Vivone
In this paper, inspired by previous work of MHIF task, we realize that HR-MSI could serve as a high-frequency detail auxiliary input, leading us to propose a novel INR-based hyperspectral fusion function named Implicit Neural Feature Fusion Function (INF).
no code implementations • 25 May 2023 • Zhenxi Zhang, Ran Ran, Chunna Tian, Heng Zhou, Fan Yang, Xin Li, Zhicheng Jiao
This paper proposes a cross-supervised learning framework based on dual classifiers (DC-Net), including an evidential classifier and a vanilla classifier.
no code implementations • 25 May 2023 • Zhenxi Zhang, Ran Ran, Chunna Tian, Heng Zhou, Xin Li, Fan Yang, Zhicheng Jiao
To address these issues, we propose a self-aware and cross-sample prototypical learning method (SCP-Net) to enhance the diversity of prediction in consistency learning by utilizing a broader range of semantic information derived from multiple inputs.
no code implementations • 10 Apr 2023 • ZiHan Cao, ShiQi Cao, Xiao Wu, JunMing Hou, Ran Ran, Liang-Jian Deng
Denosing diffusion model, as a generative model, has received a lot of attention in the field of image generation recently, thanks to its powerful generation capability.
no code implementations • 5 Feb 2023 • Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Shaoyi Huang, Xi Xie, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding
The proliferation of deep learning (DL) has led to the emergence of privacy and security concerns.
2 code implementations • 24 Sep 2022 • Ran Ran, Nuo Xu, Wei Wang, Gang Quan, Jieming Yin, Wujie Wen
To this end, we develop an approach that can effectively take advantage of the sparsity of matrix operations in GCN inference to significantly reduce the computational overhead.
no code implementations • 20 Sep 2022 • Hongwu Peng, Shanglin Zhou, Yukui Luo, Shijin Duan, Nuo Xu, Ran Ran, Shaoyi Huang, Chenghong Wang, Tong Geng, Ang Li, Wujie Wen, Xiaolin Xu, Caiwen Ding
The rapid growth and deployment of deep learning (DL) has witnessed emerging privacy and security concerns.
no code implementations • 14 Jul 2022 • Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie
Energy harvesting (EH) technology that harvests energy from ambient environment is a promising alternative to batteries for powering those devices due to the low maintenance cost and wide availability of the energy sources.
1 code implementation • 11 Jun 2022 • Nuo Xu, Binghui Wang, Ran Ran, Wujie Wen, Parv Venkitasubramaniam
Membership inference attacks (MIAs) against machine learning models can lead to serious privacy risks for the training dataset used in the model training.