Search Results for author: Jun Wei

Found 15 papers, 7 papers with code

Generative Semantic Communication for Joint Image Transmission and Segmentation

no code implementations27 Nov 2024 Weiwen Yuan, Jinke Ren, Chongjie Wang, Ruichen Zhang, Jun Wei, Dong In Kim, Shuguang Cui

Our approach builds upon semantic knowledge bases (KBs) at both the transmitter and receiver, with each semantic KB comprising a source KB and a task KB.

feature selection Image Reconstruction +3

Privacy-Preserving Federated Foundation Model for Generalist Ultrasound Artificial Intelligence

no code implementations25 Nov 2024 Yuncheng Jiang, Chun-Mei Feng, Jinke Ren, Jun Wei, Zixun Zhang, Yiwen Hu, Yunbi Liu, Rui Sun, Xuemei Tang, Juan Du, Xiang Wan, Yong Xu, Bo Du, Xin Gao, Guangyu Wang, Shaohua Zhou, Shuguang Cui, Rick Siow Mong Goh, Yong liu, Zhen Li

Notably, UltraFedFM surpasses the diagnostic accuracy of mid-level ultrasonographers and matches the performance of expert-level sonographers in the joint diagnosis of 8 common systemic diseases.

Federated Learning Lesion Segmentation +1

Let Video Teaches You More: Video-to-Image Knowledge Distillation using DEtection TRansformer for Medical Video Lesion Detection

no code implementations26 Aug 2024 Yuncheng Jiang, Zixun Zhang, Jun Wei, Chun-Mei Feng, Guanbin Li, Xiang Wan, Shuguang Cui, Zhen Li

The teacher network aims at extracting temporal contexts from multiple frames and transferring them to the student network, and the student network is an image-based model dedicated to fast prediction in inference.

Knowledge Distillation Lesion Detection

Towards a Benchmark for Colorectal Cancer Segmentation in Endorectal Ultrasound Videos: Dataset and Model Development

no code implementations19 Aug 2024 Yuncheng Jiang, Yiwen Hu, Zixun Zhang, Jun Wei, Chun-Mei Feng, Xuemei Tang, Xiang Wan, Yong liu, Shuguang Cui, Zhen Li

Based on this dataset, we further introduce a benchmark model for colorectal cancer segmentation, named the Adaptive Sparse-context TRansformer (ASTR).

Segmentation

ScribblePolyp: Scribble-Supervised Polyp Segmentation through Dual Consistency Alignment

no code implementations9 Nov 2023 Zixun Zhang, Yuncheng Jiang, Jun Wei, Hannah Cui, Zhen Li

The second branch leverages affinity propagation to refine predictions into a soft version, extending additional supervision to unlabeled pixels.

BoxPolyp:Boost Generalized Polyp Segmentation Using Extra Coarse Bounding Box Annotations

1 code implementation7 Dec 2022 Jun Wei, Yiwen Hu, Guanbin Li, Shuguang Cui, S Kevin Zhou, Zhen Li

In practice, box annotations are applied to alleviate the over-fitting issue of previous polyp segmentation models, which generate fine-grained polyp area through the iterative boosted segmentation model.

Segmentation

What is the cost of adding a constraint in linear least squares?

no code implementations24 Jan 2022 Ramakrishna Kakarala, Jun Wei

Although the theory of constrained least squares (CLS) estimation is well known, it is usually applied with the view that the constraints to be imposed are unavoidable.

Shallow Feature Matters for Weakly Supervised Object Localization

1 code implementation CVPR 2021 Jun Wei, Qin Wang, Zhen Li, Sheng Wang, S. Kevin Zhou, Shuguang Cui

In practice, our SPOL model first generates the CAMs through a novel element-wise multiplication of shallow and deep feature maps, which filters the background noise and generates sharper boundaries robustly.

Object Pseudo Label +1

Label Decoupling Framework for Salient Object Detection

1 code implementation CVPR 2020 Jun Wei, Shuhui Wang, Zhe Wu, Chi Su, Qingming Huang, Qi Tian

Though remarkable progress has been achieved, we observe that the closer the pixel is to the edge, the more difficult it is to be predicted, because edge pixels have a very imbalance distribution.

Object object-detection +3

MedSRGAN: medical images super-resolution using generative adversarial networks

1 code implementation Springer 2020 Yuchong Gu, Zitao Zen, Haibin Chen, Jun Wei, Yaqin Zhang, Binghui Chen, Yingqin Li, Yujuan Qin, Qing Xie, Zhuoren Jiang, Yao Lu

Super-resolution (SR) in medical imaging is an emerging application in medical imaging due to the needs of high quality images acquired with limited radiation dose, such as low dose Computer Tomography (CT), low field magnetic resonance imaging (MRI).

Super-Resolution

F3Net: Fusion, Feedback and Focus for Salient Object Detection

4 code implementations26 Nov 2019 Jun Wei, Shuhui Wang, Qingming Huang

Furthermore, different from binary cross entropy, the proposed PPA loss doesn't treat pixels equally, which can synthesize the local structure information of a pixel to guide the network to focus more on local details.

Camouflaged Object Segmentation Dichotomous Image Segmentation +3

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