19 citations · 26 across the 7 of their papers we have counts for
7 papers
Refined Equivalent Pinhole Model for Large-scale 3D Reconstruction from Spaceborne CCD Imagery
Hong Danyang, Yu Anzhu, Ji Song +4
In this study, we present a large-scale earth surface reconstruction pipeline for linear-array charge-coupled device (CCD) satellite imagery. While mainstream satellite image-based…
Sea Ice Extraction via Remote Sensed Imagery: Algorithms, Datasets, Applications and Challenges
Anzhu Yu, Wenjun Huang, Qing Xu +5
The deep learning, which is a dominating technique in artificial intelligence, has completely changed the image understanding over the past decade. As a consequence, the sea ice ex…
Integrating Multiple Sources Knowledge for Class Asymmetry Domain Adaptation Segmentation of Remote Sensing Images
Kuiliang Gao, Anzhu Yu, Xiong You +3
In the existing unsupervised domain adaptation (UDA) methods for remote sensing images (RSIs) semantic segmentation, class symmetry is an widely followed ideal assumption, where th…
Semi-supervised Road Updating Network (SRUNet): A Deep Learning Method for Road Updating from Remote Sensing Imagery and Historical Vector Maps
Xin Chen, Anzhu Yu, Qun Sun +3
A road is the skeleton of a city and is a fundamental and important geographical component. Currently, many countries have built geo-information databases and gathered large amount…
UAVStereo: A Multiple Resolution Dataset for Stereo Matching in UAV Scenarios
Zhang Xiaoyi, Cao Xuefeng, Yu Anzhu +3
Stereo matching is a fundamental task for 3D scene reconstruction. Recently, deep learning based methods have proven effective on some benchmark datasets, such as KITTI and Scene F…
Attention Aware Cost Volume Pyramid Based Multi-view Stereo Network for 3D Reconstruction
Anzhu Yu, Wenyue Guo, Bing Liu +4
We present an efficient multi-view stereo (MVS) network for 3D reconstruction from multiview images. While previous learning based reconstruction approaches performed quite well, m…
Active Deep Densely Connected Convolutional Network for Hyperspectral Image Classification
Bing Liu, Anzhu Yu, Pengqiang Zhang +4
Deep learning based methods have seen a massive rise in popularity for hyperspectral image classification over the past few years. However, the success of deep learning is attribut…