290 citations · 317 across the 7 of their papers we have counts for
7 papers
Cross-Modality Deep Feature Learning for Brain Tumor Segmentation
Dingwen Zhang, Guohai Huang, Qiang Zhang +3
Recent advances in machine learning and prevalence of digital medical images have opened up an opportunity to address the challenging brain tumor segmentation (BTS) task by using d…
Exploring Modality-shared Appearance Features and Modality-invariant Relation Features for Cross-modality Person Re-Identification
Nianchang Huang, Jianan Liu, Qiang Zhang +1
Most existing cross-modality person re-identification works rely on discriminative modality-shared features for reducing cross-modality variations and intra-modality variations. De…
Onfocus Detection: Identifying Individual-Camera Eye Contact from Unconstrained Images
Dingwen Zhang, Bo Wang, Gerong Wang +4
Onfocus detection aims at identifying whether the focus of the individual captured by a camera is on the camera or not. Based on the behavioral research, the focus of an individual…
Densely Nested Top-Down Flows for Salient Object Detection
Chaowei Fang, Haibin Tian, Dingwen Zhang +3
With the goal of identifying pixel-wise salient object regions from each input image, salient object detection (SOD) has been receiving great attention in recent years. One kind of…
GFCN: A New Graph Convolutional Network Based on Parallel Flows
Feng Ji, Jielong Yang, Qiang Zhang +1
In view of the huge success of convolution neural networks (CNN) for image classification and object recognition, there have been attempts to generalize the method to general graph…
Sparse Representation based Multi-sensor Image Fusion: A Review
Qiang Zhang, Yi Liu, Rick S. Blum +2
As a result of several successful applications in computer vision and image processing, sparse representation (SR) has attracted significant attention in multi-sensor image fusion.…
Unsupervised Video Analysis Based on a Spatiotemporal Saliency Detector
Qiang Zhang, Yilin Wang, Baoxin Li
Visual saliency, which predicts regions in the field of view that draw the most visual attention, has attracted a lot of interest from researchers. It has already been used in seve…