MPFFNet:Semantic Segmentation of Remote Sensing Image Buildings Based on Multipath Feature Fusion-Reference-Cited by-同舟云学术

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MPFFNet:Semantic Segmentation of Remote Sensing Image Buildings Based on Multipath Feature Fusion

Published:2023-11-17 Issue: Volume: Page:
ISSN:
Container-title:2023 8th International Conference on Communication, Image and Signal Processing (CCISP)
language:
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Author:

Dong Jie¹,Mao Jingkun¹,Liu Kun²,Cheng Liangyong³

Affiliation:

1. School of Electrical Engineering and Automation, Tianjin University of Technology,Tianjin,China

2. School of Artificial Intelligence and Data Science, Hebei University of Technology,Tianjin,China

3. Interplanetary Space Technology Development Co. LTD,Tianjin,China

Funder

National Natural Science Foundation of China (General Program)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10355681/10355682/10355804.pdf?arnumber=10355804

Reference10 articles.

1. Segmentation of High Spatial Resolution Remote Sensing Image based On U-Net Convolutional Networks

2. Boundary Enhancement Semantic Segmentation for Building Extraction From Remote Sensed Image

3. EANet: Edge-Aware Network for the Extraction of Buildings from Aerial Images

4. Based on the improved Deeplabv3 + remote sensing image semantic segmentation algorithm

5. Automatic Building Extraction on High-Resolution Remote Sensing Imagery Using Deep Convolutional Encoder-Decoder With Spatial Pyramid Pooling

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