A full-attention network with an open dataset for large-scale building semantic segmentation along long-span high-speed rail lines-Reference-Cited by-同舟云学术

A full-attention network with an open dataset for large-scale building semantic segmentation along long-span high-speed rail lines

Published:2024-08-30 Issue:1 Volume:17 Page:
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Qiao Wenfan¹²,Shen Li¹²,Wang Jicheng³,Li Zhilin¹²

Affiliation:

1. State-Province Joint Engineering Laboratory of Spatial Information Technology for High-Speed Railway Safety, Southwest Jiaotong University, Chengdu, People's Republic of China

2. Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, People's Republic of China

3. Key Laboratory of Ministry of Education on Land Resources Evaluation and Monitoring in Southwest China, Sichuan Normal University, Chengdu, People's Republic of China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

MiaoZi Project of Sichuan Province in China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2393265

Reference71 articles.

1. IMPROVED BUILDING DETECTION USING TEXTURE INFORMATION

2. IEEE Transactions on Pattern Analysis and Machine Intelligence

3. Deep learning-based multi-feature semantic segmentation in building extraction from images of UAV photogrammetry

4. TEMPORARY REMOVAL: Aerial imagery for roof segmentation: A large-scale dataset towards automatic mapping of buildings

5. Chen Liang-Chieh Yukun Zhu George Papandreou Florian Schroff and Hartwig Adam. 2018. “Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.” In Proceedings of the European Conference on Computer Vision (ECCV) 801–818 Munich Germany.