Receptive Convolution Boosts Large-Scale Multi-Class Change Detection-Reference-Cited by-同舟云学术

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Receptive Convolution Boosts Large-Scale Multi-Class Change Detection

Published:2024-07-07 Issue: Volume: Page:10459-10462
ISSN:
Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Yuan Shuai¹,Wei Fan²,Zhang Lixian³,Fu Haohuan³,Gong Peng¹

Affiliation:

1. The University of Hong Kong,Department of Geography,Hong Kong,China

2. Huazhong University of Science and Technology,School of Mathematics and Statistics,Wuhan,China

3. Tsinghua University,Ministry of Education Key Laboratory for Earth System Modeling,Department of Earth System Science,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10642081.pdf?arnumber=10642081

Reference13 articles.

1. Change Detection Based on Artificial Intelligence: State-of-the-Art and Challenges

2. Transitioning from change detection to monitoring with remote sensing: A paradigm shift

3. An automatic change detection method for monitoring newly constructed building areas using time-series multi-view high-resolution optical satellite images

4. Near-real time forest change detection using PlanetScope imagery

5. Toward a Generalizable Image Representation for Large-Scale Change Detection: Application to Generic Damage Analysis

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