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Shiqing Wei
Researcher at Wuhan University
Publications - 10
Citations - 1137
Shiqing Wei is an academic researcher from Wuhan University. The author has contributed to research in topics: Computer science & Convolutional neural network. The author has an hindex of 6, co-authored 7 publications receiving 359 citations.
Papers
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Journal ArticleDOI
Fully Convolutional Networks for Multisource Building Extraction From an Open Aerial and Satellite Imagery Data Set
Shunping Ji,Shiqing Wei,Meng Lu +2 more
TL;DR: The Siamese U-Net outperforms current building extraction methods and could provide valuable reference and the designed experiments indicate the data set is accurate and can serve multiple purposes including building instance segmentation and change detection.
Journal ArticleDOI
Toward Automatic Building Footprint Delineation From Aerial Images Using CNN and Regularization
Shiqing Wei,Shunping Ji,Meng Lu +2 more
TL;DR: This study proposes an automatic building footprint extraction framework that consists of a convolutional neural network (CNN)-based segmentation and an empirical polygon regularization that transforms segmentation maps into structured individual building polygons.
Journal ArticleDOI
A scale robust convolutional neural network for automatic building extraction from aerial and satellite imagery
Shunping Ji,Shiqing Wei,Meng Lu +2 more
TL;DR: This study develops a scale robust CNN structure to improve the segmentation accuracy of building data from high-resolution aerial and satellite images and introduces a combined data augmentation and relative radiometric calibration method for multi-source building extraction.
Journal ArticleDOI
Detecting Large-Scale Urban Land Cover Changes from Very High Resolution Remote Sensing Images Using CNN-Based Classification
TL;DR: Testing results showed that the FACNN greatly exceeded several recent convolutional neural networks in land cover classification and the object-based change detection could achieve much better results than a pixel-based method, and provide accurate change maps to facilitate manual urban land cover updating.
Journal ArticleDOI
Automatic 3D building reconstruction from multi-view aerial images with deep learning
TL;DR: A new fully automatic three-dimensional building reconstruction method that can generate first level of detail (LoD 1) building models from multi-view aerial images without any assistance from other data is introduced.