no code implementations • 10 May 2024 • Chenhao Xu, Yudian Zhang, Kaiye Xu, Haijiang Zhu
Accurate polyp segmentation is crucial for the early detection and prevention of colorectal cancer.
no code implementations • 9 May 2024 • Yudian Zhang, Chenhao Xu, Kaiye Xu, Haijiang Zhu
Lots of popular calibration methods in medical images focus on classification, but there are few comparable studies on semantic segmentation.
2 code implementations • 8 Apr 2024 • Chenhao Xu, Chang-Tsun Li, Chee Peng Lim, Douglas Creighton
While the Vision Transformer (ViT) architecture gains prominence in computer vision and attracts significant attention from multimedia communities, its deficiency in prior knowledge (inductive bias) regarding shift, scale, and rotational invariance necessitates pre-training on large-scale datasets.
no code implementations • 19 Oct 2023 • Chenhao Xu, Chang-Tsun Li, Yongjian Hu, Chee Peng Lim, Douglas Creighton
Video instance segmentation, also known as multi-object tracking and segmentation, is an emerging computer vision research area introduced in 2019, aiming at detecting, segmenting, and tracking instances in videos simultaneously.
1 code implementation • 15 Aug 2022 • Chenhao Xu, Youyang Qu, Tom H. Luan, Peter W. Eklund, Yong Xiang, Longxiang Gao
Asynchronous Federated Learning (AFL) is a scheme that reduces the latency of aggregation to improve efficiency, but the learning performance is unstable due to unreasonably weighted local models.
no code implementations • 12 Mar 2021 • Chenhao Xu, Jiaqi Ge, Yong Li, Yao Deng, Longxiang Gao, Mengshi Zhang, Yong Xiang, Xi Zheng
Federated learning (FL) enables collaborative training of a shared model on edge devices while maintaining data privacy.
no code implementations • 27 Sep 2016 • Yanyan Geng, Ru-Ze Liang, Weizhi Li, Jingbin Wang, Gaoyuan Liang, Chenhao Xu, Jing-Yan Wang
The CNN model is used to represent the multi-instance data point, and a classifier function is used to predict the label from the its CNN representation.