no code implementations • 22 Feb 2024 • Zhiyuan Wang, Jinhao Duan, Chenxi Yuan, Qingyu Chen, Tianlong Chen, Huaxiu Yao, Yue Zhang, Ren Wang, Kaidi Xu, Xiaoshuang Shi
Uncertainty estimation plays a pivotal role in ensuring the reliability of safety-critical human-AI interaction systems, particularly in the medical domain.
no code implementations • 23 Nov 2023 • Fei Kong, Jinhao Duan, Lichao Sun, Hao Cheng, Renjing Xu, HengTao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu
Though diffusion models excel in image generation, their step-by-step denoising leads to slow generation speeds.
1 code implementation • 3 Aug 2023 • Lu Zeng, Xuan Chen, Xiaoshuang Shi, Heng Tao Shen
In this study, we introduce and theoretically demonstrate a simple feature noise method, which directly adds noise to the features of training data, can enhance the generalization of DNNs under label noise.
no code implementations • 12 Jul 2023 • RuiPeng Ma, Jinhao Duan, Fei Kong, Xiaoshuang Shi, Kaidi Xu
Image synthesis has seen significant advancements with the advent of diffusion-based generative models like Denoising Diffusion Probabilistic Models (DDPM) and text-to-image diffusion models.
no code implementations • 28 May 2023 • Jin Sun, Xiaoshuang Shi, Zhiyuan Wang, Kaidi Xu, Heng Tao Shen, Xiaofeng Zhu
Then, we build a pure-MLP architecture called Caterpillar by replacing the convolutional layer with the SPC module in a hybrid model of sMLPNet.
1 code implementation • 26 May 2023 • Fei Kong, Jinhao Duan, RuiPeng Ma, HengTao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu
Therefore, we also explore the robustness of diffusion models to MIA in the text-to-speech (TTS) task, which is an audio generation task.
no code implementations • 28 Apr 2023 • Jinhao Duan, Quanfu Fan, Hao Cheng, Xiaoshuang Shi, Kaidi Xu
In this paper, we introduce Temporal Adversarial Augmentation (TA), a novel video augmentation technique that utilizes temporal attention.
1 code implementation • 2 Feb 2023 • Jinhao Duan, Fei Kong, Shiqi Wang, Xiaoshuang Shi, Kaidi Xu
In this paper, we investigate the vulnerability of diffusion models to Membership Inference Attacks (MIAs), a common privacy concern.
1 code implementation • 7 May 2021 • Xiaoshuang Shi, Zhenhua Guo, Kang Li, Yun Liang, Xiaofeng Zhu
They might significantly deteriorate the performance of convolutional neural networks (CNNs), because CNNs are easily overfitted on corrupted labels.
no code implementations • 3 Jul 2018 • Jinzheng Cai, Le Lu, Adam P. Harrison, Xiaoshuang Shi, Pingjun Chen, Lin Yang
Given image labels as the only supervisory signal, we focus on harvesting, or mining, thoracic disease localizations from chest X-ray images.
no code implementations • 24 Aug 2017 • Zizhao Zhang, Fuyong Xing, Hai Su, Xiaoshuang Shi, Lin Yang
Then we review their recent applications in medical image analysis and point out limitations, with the goal to light some potential directions in medical image analysis.
no code implementations • 18 Feb 2017 • Zizhao Zhang, Fuyong Xing, Hanzi Wang, Yan Yan, Ying Huang, Xiaoshuang Shi, Lin Yang
In this paper, we propose a simple but effective method for fast image segmentation.
no code implementations • CVPR 2016 • Zizhao Zhang, Fuyong Xing, Xiaoshuang Shi, Lin Yang
In this paper, we investigate the usage of semi-supervised learning (SSL) to obtain competitive detection accuracy with very limited training data (three labeled images).