1.9k citations · 5.3k across the 34 of their papers we have counts for
12 papers · 1 filter
NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote Sensing Imagery
Ming Lu, Leyuan Fang, Muxing Li +3
The use of deep learning for water extraction requires precise pixel-level labels. However, it is very difficult to label high-resolution remote sensing images at the pixel level.…
PointShuffleNet: Learning Non-Euclidean Features with Homotopy Equivalence and Mutual Information
Linchao He, Mengting Luo, Dejun Zhang +3
Point cloud analysis is still a challenging task due to the disorder and sparsity of samplings of their geometric structures from 3D sensors. In this paper, we introduce the homoto…
Hyper RPCA: Joint Maximum Correntropy Criterion and Laplacian Scale Mixture Modeling On-the-Fly for Moving Object Detection
Zerui Shao, Yifei Pu, Jiliu Zhou +2
Moving object detection is critical for automated video analysis in many vision-related tasks, such as surveillance tracking, video compression coding, etc. Robust Principal Compon…
Three-dimensional Optical Coherence Tomography Image Denoising through Multi-input Fully-Convolutional Networks
Ashkan Abbasi, Amirhassan Monadjemi, Leyuan Fang +2
In recent years, there has been a growing interest in applying convolutional neural networks (CNNs) to low-level vision tasks such as denoising and super-resolution. Due to the coh…
Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising
Chenyu You, Qingsong Yang, Hongming Shan +8
Computed tomography (CT) is a popular medical imaging modality in clinical applications. At the same time, the x-ray radiation dose associated with CT scans raises public concerns…
3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network
Hongming Shan, Yi Zhang, Qingsong Yang +5
Low-dose computed tomography (CT) has attracted a major attention in the medical imaging field, since CT-associated x-ray radiation carries health risks for patients. The reduction…
Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss
Qingsong Yang, Pingkun Yan, Yanbo Zhang +5
In this paper, we introduce a new CT image denoising method based on the generative adversarial network (GAN) with Wasserstein distance and perceptual similarity. The Wasserstein d…
Effective face landmark localization via single deep network
Zongping Deng, Ke Li, Qijun Zhao +2
In this paper, we propose a novel face alignment method using single deep network (SDN) on existing limited training data. Rather than using a max-pooling layer followed one convol…
Connections Between Nuclear Norm and Frobenius Norm Based Representations
Xi Peng, Canyi Lu, Zhang Yi +1
A lot of works have shown that frobenius-norm based representation (FNR) is competitive to sparse representation and nuclear-norm based representation (NNR) in numerous tasks such…
Automatic Subspace Learning via Principal Coefficients Embedding
Xi Peng, Jiwen Lu, Zhang Yi +1
In this paper, we address two challenging problems in unsupervised subspace learning: 1) how to automatically identify the feature dimension of the learned subspace (i.e., automati…
Learning Locality-Constrained Collaborative Representation for Face Recognition
Xi Peng, Lei Zhang, Zhang Yi +1
The model of low-dimensional manifold and sparse representation are two well-known concise models that suggest each data can be described by a few characteristics. Manifold learnin…
Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering
Xi Peng, Zhiding Yu, Huajin Tang +1
Under the framework of graph-based learning, the key to robust subspace clustering and subspace learning is to obtain a good similarity graph that eliminates the effects of errors…