228 citations · 348 across the 14 of their papers we have counts for
14 papers
SupWMA: Consistent and Efficient Tractography Parcellation of Superficial White Matter with Deep Learning
Tengfei Xue, Fan Zhang, Chaoyi Zhang +6
White matter parcellation classifies tractography streamlines into clusters or anatomically meaningful tracts to enable quantification and visualization. Most parcellation methods…
Efficient Context-Aware Network for Abdominal Multi-organ Segmentation
Fan Zhang, Yu Wang, Hua Yang
The contextual information, presented in abdominal CT scan, is relative consistent. In order to make full use of the overall 3D context, we develop a whole-volume-based coarse-to-f…
Grasp-Oriented Fine-grained Cloth Segmentation without Real Supervision
Ruijie Ren, Mohit Gurnani Rajesh, Jordi Sanchez-Riera +6
Automatically detecting graspable regions from a single depth image is a key ingredient in cloth manipulation. The large variability of cloth deformations has motivated most of the…
DSNet: A Dual-Stream Framework for Weakly-Supervised Gigapixel Pathology Image Analysis
Tiange Xiang, Yang Song, Chaoyi Zhang +6
We present a novel weakly-supervised framework for classifying whole slide images (WSIs). WSIs, due to their gigapixel resolution, are commonly processed by patch-wise classificati…
An explainable two-dimensional single model deep learning approach for Alzheimer's disease diagnosis and brain atrophy localization
Fan Zhang, Bo Pan, Pengfei Shao +4
Early and accurate diagnosis of Alzheimer's disease (AD) and its prodromal period mild cognitive impairment (MCI) is essential for the delayed disease progression and the improved…
Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation
Yuqian Chen, Chaoyi Zhang, Yang Song +5
White matter fiber clustering (WMFC) enables parcellation of white matter tractography for applications such as disease classification and anatomical tract segmentation. However, t…
Deception Detection in Videos using the Facial Action Coding System
Hammad Ud Din Ahmed, Usama Ijaz Bajwa, Fan Zhang +1
Facts are important in decision making in every situation, which is why it is important to catch deceptive information before they are accepted as facts. Deception detection in vid…
Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin +1
We consider the task of enforcing individual fairness in gradient boosting. Gradient boosting is a popular method for machine learning from tabular data, which arise often in appli…
Single Model Deep Learning on Imbalanced Small Datasets for Skin Lesion Classification
Peng Yao, Shuwei Shen, Mengjuan Xu +6
Deep convolutional neural network (DCNN) models have been widely explored for skin disease diagnosis and some of them have achieved the diagnostic outcomes comparable or even super…
Low-cost and high-performance data augmentation for deep-learning-based skin lesion classification
Shuwei Shen, Mengjuan Xu, Fan Zhang +8
Although deep convolutional neural networks (DCNNs) have achieved significant accuracy in skin lesion classification comparable or even superior to those of dermatologists, practic…
Defending Model Inversion and Membership Inference Attacks via Prediction Purification
Ziqi Yang, Bin Shao, Bohan Xuan +2
Neural networks are susceptible to data inference attacks such as the model inversion attack and the membership inference attack, where the attacker could infer the reconstruction…
Concurrently Extrapolating and Interpolating Networks for Continuous Model Generation
Lijun Zhao, Jinjing Zhang, Fan Zhang +3
Most deep image smoothing operators are always trained repetitively when different explicit structure-texture pairs are employed as label images for each algorithm configured with…
Quantifying Legibility of Indoor Spaces Using Deep Convolutional Neural Networks: Case Studies in Train Stations
Zhoutong Wang, Qianhui Liang, Fabio Duarte +5
Legibility is the extent to which a space can be easily recognized. Evaluating legibility is particularly desirable in indoor spaces, since it has a large impact on human behavior…
Indoor Space Recognition using Deep Convolutional Neural Network: A Case Study at MIT Campus
Fan Zhang, Fabio Duarte, Ruixian Ma +3
In this paper, we propose a robust and parsimonious approach using Deep Convolutional Neural Network (DCNN) to recognize and interpret interior space. DCNN has achieved incredible…