Leveraging adaptive spatial shifts multi-layer perceptron with parameterized spatial offsets for hyperspectral image classification-Reference-Cited by-同舟云学术

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Leveraging adaptive spatial shifts multi-layer perceptron with parameterized spatial offsets for hyperspectral image classification

Published:2024-02-13 Issue:4 Volume:45 Page:1385-1417
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Ma Qiaoyu¹^ORCID,Zhou Heng¹^ORCID,Zhang Zitong²,Jiang Yanan³,Zhang Chunlei⁴^ORCID

Affiliation:

1. College of Information and Electrical Engineering, China Agricultural University, Beijing, China

2. School of Earth Sciences and Resources, China University of Geosciences, Beijing, China

3. School of Mathematical Sciences, Beijing Normal University, Beijing, China

4. Beijing Zhongdi Runde Petroleum Technology Co, Ltd, Beijing, China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2024.2311790

Reference56 articles.

1. Hyperspectral Vision Based Probe for In Situ Corrosion Monitoring in Saline Environments

2. Deep Learning for Classification of Hyperspectral Data: A Comparative Review

3. Local sensitive discriminative broad learning system for hyperspectral image classification

4. Chen, S., E. Xie, C. Ge, R. Chen, D. Liang, and P. Luo. 2022. “CycleMLP: A MLP-Like Architecture for Dense Prediction.” In The Tenth International Conference on Learning Representations, Virtual, Online, 1–21.

5. Evaluation of surface reflectance bandpass adjustment techniques

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