Joint Classification of Multi-Source Remote Sensing Data Based on Multi-Scale Features and Attention Mechanism-Reference-Cited by-同舟云学术

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Joint Classification of Multi-Source Remote Sensing Data Based on Multi-Scale Features and Attention Mechanism

Published:2023-11-24 Issue: Volume:26 Page:86-92
ISSN:
Container-title:Proceedings of the 2023 5th International Conference on Video, Signal and Image Processing
language:
Short-container-title:

Author:

Zhang Beibei¹^ORCID,Zhang Tao²^ORCID,Zhang Yu²^ORCID,Zhao Duo²^ORCID,Ye Zhen²^ORCID

Affiliation:

1. Chinese Flight Test Establishment, AVIC, China

2. School of Electronics and Control Engineering, Chang'an University, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3638682.3638699

Reference19 articles.

1. Hyperspectral image assessment of oil‐contaminated wetland;Salem F.;International Journal of Remote Sensing,2005

2. Hyperspectral Imaging Applications in Agriculture and Agro-Food Product Quality and Safety Control: A Review

3. Deep learning-based hyperspectral image classification with application o environmental geographic information systems;Song A.;Korean Journal of Remote Sensing,2017

4. Briottet X., Boucher Y., Dimmeler A., Reulke R., Suomalainen J., Mueller A., Holzwarth S., Strobl P., Bulatov D., Richter R., Schlapfer D. Military applications of hyperspectral imagery Targets and backgrounds XII: Characterization and representation. SPIE, 2006, 6239: 82-89.

5. Deep Learning-Based Classification of Hyperspectral Data

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