207 citations · 466 across the 18 of their papers we have counts for
4 papers · 1 filter
Discriminative Adversarial Domain Adaptation
Hui Tang, Kui Jia
Given labeled instances on a source domain and unlabeled ones on a target domain, unsupervised domain adaptation aims to learn a task classifier that can well classify target insta…
Shape-Aware Organ Segmentation by Predicting Signed Distance Maps
Yuan Xue, Hui Tang, Zhi Qiao +6
In this work, we propose to resolve the issue existing in current deep learning based organ segmentation systems that they often produce results that do not capture the overall sha…
Object-Guided Instance Segmentation for Biological Images
Jingru Yi, Hui Tang, Pengxiang Wu +5
Instance segmentation of biological images is essential for studying object behaviors and properties. The challenges, such as clustering, occlusion, and adhesion problems of the ob…
Domain-Symmetric Networks for Adversarial Domain Adaptation
Yabin Zhang, Hui Tang, Kui Jia +1
Unsupervised domain adaptation aims to learn a model of classifier for unlabeled samples on the target domain, given training data of labeled samples on the source domain. Impressi…