316 citations · 2.9k across the 50 of their papers we have counts for
5 papers · 1 filter
3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training
Yingda Xia, Fengze Liu, Dong Yang +6
While making a tremendous impact in various fields, deep neural networks usually require large amounts of labeled data for training which are expensive to collect in many applicati…
Semi-supervised Skin Lesion Segmentation via Transformation Consistent Self-ensembling Model
Xiaomeng Li, Lequan Yu, Hao Chen +2
Automatic skin lesion segmentation on dermoscopic images is an essential component in computer-aided diagnosis of melanoma. Recently, many fully supervised deep learning based meth…
EC-Net: an Edge-aware Point set Consolidation Network
Lequan Yu, Xianzhi Li, Chi-Wing Fu +2
Point clouds obtained from 3D scans are typically sparse, irregular, and noisy, and required to be consolidated. In this paper, we present the first deep learning based edge-aware…
Deeply Supervised Rotation Equivariant Network for Lesion Segmentation in Dermoscopy Images
Xiaomeng Li, Lequan Yu, Chi-Wing Fu +1
Automatic lesion segmentation in dermoscopy images is an essential step for computer-aided diagnosis of melanoma. The dermoscopy images exhibits rotational and reflectional symmetr…
PU-Net: Point Cloud Upsampling Network
Lequan Yu, Xianzhi Li, Chi-Wing Fu +2
Learning and analyzing 3D point clouds with deep networks is challenging due to the sparseness and irregularity of the data. In this paper, we present a data-driven point cloud ups…