Building Extraction from Remote Sensing Images Using SegNet

Hongshun Chen; Shilin Lu

doi:10.1109/icivc47709.2019.8981046

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JOURNAL ARTICLE

Building Extraction from Remote Sensing Images Using SegNet

Hongshun Chen Shilin Lu

Year: 2019 Pages: 227-230

DOI: 10.1109/icivc47709.2019.8981046

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Abstract

Automated building extraction from remote sensing images is one of the most challenging problems. SegNet is an efficient architecture for pixel-wise semantic segmentation.We improved SegNet and test it on the Inria aerial image labeling dataset, results show that the improved one performance better.

Keywords:

Computer science Artificial intelligence Segmentation Pixel Computer vision Image segmentation Extraction (chemistry) Feature extraction Pattern recognition (psychology) Image (mathematics) Remote sensing Geology

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Topics

Remote-Sensing Image Classification

Physical Sciences → Engineering → Media Technology

Automated Road and Building Extraction

Physical Sciences → Engineering → Ocean Engineering

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Building Extraction from Remote Sensing Images Using SegNet

Abstract

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