6 citations · 6 across the 3 of their papers we have counts for
6 papers
Graph Neural Networks for UnsupervisedDomain Adaptation of Histopathological ImageAnalytics
Dou Xu, Chang Cai, Chaowei Fang +3
Annotating histopathological images is a time-consuming andlabor-intensive process, which requires broad-certificated pathologistscarefully examining large-scale whole-slide images…
Category-wise Attack: Transferable Adversarial Examples for Anchor Free Object Detection
Quanyu Liao, Xin Wang, Bin Kong +4
Deep neural networks have been demonstrated to be vulnerable to adversarial attacks: subtle perturbations can completely change the classification results. Their vulnerability has…
Domain Embedded Multi-model Generative Adversarial Networks for Image-based Face Inpainting
Xian Zhang, Xin Wang, Bin Kong +6
Prior knowledge of face shape and structure plays an important role in face inpainting. However, traditional face inpainting methods mainly focus on the generated image resolution…
CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation
Peng Liu, Bin Kong, Zhongyu Li +2
Recently, deep neural networks have demonstrated comparable and even better performance with board-certified ophthalmologists in well-annotated datasets. However, the diversity of…
Attention-driven Tree-structured Convolutional LSTM for High Dimensional Data Understanding
Bin Kong, Xin Wang, Junjie Bai +7
Modeling the sequential information of image sequences has been a vital step of various vision tasks and convolutional long short-term memory (ConvLSTM) has demonstrated its superb…
Residual Attention based Network for Hand Bone Age Assessment
Eric Wu, Bin Kong, Xin Wang +8
Computerized automatic methods have been employed to boost the productivity as well as objectiveness of hand bone age assessment. These approaches make predictions according to the…