Deep Self-Supervised Pixel-Level Learning For Hyperspectral Classification-Reference-Cited by-同舟云学术

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Deep Self-Supervised Pixel-Level Learning For Hyperspectral Classification

Published:2022-09-13 Issue: Volume: Page:
ISSN:
Container-title:2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
language:
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Author:

Gonzalez-Santiago Jonathan¹,Schenkel Fabian¹,Gross Wolfgang¹,Middelmann Wolfgang¹

Affiliation:

1. Fraunhofer IOSB, Gutleuthausstr. 1,Ettlingen,Germany,76275

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9955031/9955024/09955106.pdf?arnumber=9955106

Reference11 articles.

1. Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning

2. Self-supervised vision transformers for land-cover seg Fig. 2. Classification results for Greding with 10% labels. mentation and classification;scheibenreif;Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops,2022

3. Hyperspectral remote sensing scenes;graña,2022

4. Momentum contrast for unsupervised visual representation learning;kaiming;2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),2020

5. ImageNet: A large-scale hierarchical image database

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Feedforward Neural Network Classification of Tree Species Using Hyperspectral Imagery;2023 Communication and Information Technologies (KIT);2023-10-11

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