1 code implementation • 5 Dec 2023 • Jiayi Chen, Benteng Ma, Hengfei Cui, Yong Xia
Extensive experiments and analysis on five real multi-center medical image datasets demonstrate the superiority of FEAL over the state-of-the-art active learning methods in federated scenarios with domain shifts.
no code implementations • 23 Sep 2023 • Xiaoyu Bai, Benteng Ma, Changyang Li, Yong Xia
Pseudo-label-based methods examine the training data and mine unlabelled objects for retraining, which have shown to be effective to tackle this issue.
no code implementations • 6 Aug 2022 • Benteng Ma, Yushi Wang, Shen Wang
Approaches evaluated include the Adversarial Co-training Network (ACN) and a combination of mmGAN and DeepMedic.
3 code implementations • CVPR 2022 • Yu Feng, Benteng Ma, Jing Zhang, Shanshan Zhao, Yong Xia, DaCheng Tao
However, designing a unified BA method that can be applied to various MIA systems is challenging due to the diversity of imaging modalities (e. g., X-Ray, CT, and MRI) and analysis tasks (e. g., classification, detection, and segmentation).
1 code implementation • NeurIPS 2020 • Benteng Ma, Jing Zhang, Yong Xia, DaCheng Tao
Attention modules have been demonstrated effective in strengthening the representation ability of a neural network via reweighting spatial or channel features or stacking both operations sequentially.
1 code implementation • 30 Nov 2020 • Benteng Ma, Jing Zhang, Yong Xia, DaCheng Tao
Differential Neural Architecture Search (NAS) methods represent the network architecture as a repetitive proxy directed acyclic graph (DAG) and optimize the network weights and architecture weights alternatively in a differential manner.
no code implementations • 1 Jul 2018 • Benteng Ma, Yong Xia
Recent years have witnessed the breakthrough success of deep convolutional neural networks (DCNNs) in image classification and other vision applications.
no code implementations • 28 Apr 2017 • Benteng Ma, Yong Xia
In this paper, a tribe competition-based genetic algorithm (TCbGA) is proposed for feature selection in pattern classification.