1 code implementation • 17 Feb 2024 • Yulong Shi, Mingwei Sun, Yongshuai Wang, Rui Wang, Hui Sun, Zengqiang Chen
Vision transformers have achieved encouraging progress in various computer vision tasks.
1 code implementation • 20 Nov 2023 • Jin Ye, Junlong Cheng, Jianpin Chen, Zhongying Deng, Tianbin Li, Haoyu Wang, Yanzhou Su, Ziyan Huang, Jilong Chen, Lei Jiang, Hui Sun, Min Zhu, Shaoting Zhang, Junjun He, Yu Qiao
Segment Anything Model (SAM) has achieved impressive results for natural image segmentation with input prompts such as points and bounding boxes.
no code implementations • 27 Oct 2023 • Hui Sun, Hao Luo, Feifei Wang, Qingjiu Chen, Meng Chen, Xiaoduo Wang, Haibo Yu, Guanglie Zhang, Lianqing Liu, JianPing Wang, Dapeng Wu, Wen Jung Li
Scanning electron microscopy (SEM) is indispensable in diverse applications ranging from microelectronics to food processing because it provides large depth-of-field images with a resolution beyond the optical diffraction limit.
2 code implementations • 7 Sep 2023 • Ziyan Huang, Zhongying Deng, Jin Ye, Haoyu Wang, Yanzhou Su, Tianbin Li, Hui Sun, Junlong Cheng, Jianpin Chen, Junjun He, Yun Gu, Shaoting Zhang, Lixu Gu, Yu Qiao
To address these questions, we introduce A-Eval, a benchmark for the cross-dataset Evaluation ('Eval') of Abdominal ('A') multi-organ segmentation.
no code implementations • 30 Aug 2023 • Zhen Zhang, Hongrui Sun, Hui Sun
Capacity attenuation is one of the most intractable issues in the current of application of the cells.
3 code implementations • 30 Aug 2023 • Junlong Cheng, Jin Ye, Zhongying Deng, Jianpin Chen, Tianbin Li, Haoyu Wang, Yanzhou Su, Ziyan Huang, Jilong Chen, Lei Jiang, Hui Sun, Junjun He, Shaoting Zhang, Min Zhu, Yu Qiao
To bridge this gap, we introduce SAM-Med2D, the most comprehensive studies on applying SAM to medical 2D images.
no code implementations • 19 Aug 2023 • Hui Sun, Tianqing Zhu, Wenhan Chang, Wanlei Zhou
Based on the substitution mechanism and fake label, we propose a cascaded unlearning approach for both item and class unlearning within GAN models, in which the unlearning and learning processes run in a cascaded manner.
no code implementations • 13 Apr 2023 • Ziyan Huang, Haoyu Wang, Zhongying Deng, Jin Ye, Yanzhou Su, Hui Sun, Junjun He, Yun Gu, Lixu Gu, Shaoting Zhang, Yu Qiao
However, the state-of-the-art models for medical image segmentation are still small-scale, with their parameters only in the tens of millions.
no code implementations • 3 Feb 2023 • Yizhou Chen, Guangda Huzhang, AnXiang Zeng, Qingtao Yu, Hui Sun, Heng-yi Li, Jingyi Li, Yabo Ni, Han Yu, Zhiming Zhou
However, such a method has two important limitations in real-world applications: 1) it is hard to learn embeddings that generalize well for users and items with rare interactions on their own; and 2) it may incur unbearably high memory costs when the number of users and items scales up.
1 code implementation • 17 Dec 2022 • Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun
In this paper, we carry out numerical analysis to prove convergence of a novel sample-wise back-propagation method for training a class of stochastic neural networks (SNNs).
1 code implementation • 9 Dec 2020 • Shanshan Wang, Cheng Li, Rongpin Wang, Zaiyi Liu, Meiyun Wang, Hongna Tan, Yaping Wu, Xinfeng Liu, Hui Sun, Rui Yang, Xin Liu, Jie Chen, Huihui Zhou, Ismail Ben Ayed, Hairong Zheng
Automatic medical image segmentation plays a critical role in scientific research and medical care.
no code implementations • 6 Aug 2019 • Cheng Li, Hui Sun, Zaiyi Liu, Meiyun Wang, Hairong Zheng, Shan-Shan Wang
From the different modalities, one modality that contributes most to the results is selected as the master modality, which supervises the information selection of the other assistant modalities.
no code implementations • 24 Oct 2018 • Hui Sun, Cheng Li, Boqiang Liu, Hairong Zheng, David Dagan Feng, Shan-Shan Wang
In AUNet, we employ an asymmetrical encoder-decoder structure and propose an effective upsampling block, attention-guided dense-upsampling block (AU block).