Self-supervised learning in remote sensing: A review
Y Wang, CM Albrecht, NAA Braham… - IEEE Geoscience and …, 2022 - ieeexplore.ieee.org
In deep learning research, self-supervised learning (SSL) has received great attention,
triggering interest within both the computer vision and remote sensing communities. While …
triggering interest within both the computer vision and remote sensing communities. While …
Perceiving spectral variation: Unsupervised spectrum motion feature learning for hyperspectral image classification
Y Sun, B Liu, X Yu, A Yu, K Gao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In recent years, deep-learning-based hyperspectral image (HSI) classification methods have
achieved significant development. The superior capability of feature extraction from these …
achieved significant development. The superior capability of feature extraction from these …
Self-supervised locality preserving low-pass graph convolutional embedding for large-scale hyperspectral image clustering
Y Ding, Z Zhang, X Zhao, Y Cai, S Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Due to prior knowledge deficiency, large spectral variability, and high dimension of
hyperspectral image (HSI), HSI clustering is extremally a fundamental but challenging task …
hyperspectral image (HSI), HSI clustering is extremally a fundamental but challenging task …
Unsupervised self-correlated learning smoothy enhanced locality preserving graph convolution embedding clustering for hyperspectral images
Y Ding, Z Zhang, X Zhao, W Cai, N Yang… - … on Geoscience and …, 2022 - ieeexplore.ieee.org
Hyperspectral image (HSI) clustering is an extremely fundamental but challenging task with
no labeled samples. Deep clustering methods have attracted increasing attention and have …
no labeled samples. Deep clustering methods have attracted increasing attention and have …
Category-specific prototype self-refinement contrastive learning for few-shot hyperspectral image classification
Deep learning (DL) has been extensively used for hyperspectral image classification (HSIC)
with significant success, but the classification of high-dimensional hyperspectral image (HSI) …
with significant success, but the classification of high-dimensional hyperspectral image (HSI) …
A semisupervised Siamese network for hyperspectral image classification
With the development of hyperspectral imaging technology, hyperspectral images (HSIs)
have become important when analyzing the class of ground objects. In recent years …
have become important when analyzing the class of ground objects. In recent years …
Nearest neighboring self-supervised learning for hyperspectral image classification
Recently, state-of-the-art classification performance of natural images has been obtained by
self-supervised learning (S2L) as it can generate latent features through learning between …
self-supervised learning (S2L) as it can generate latent features through learning between …
Contrastive multi-view subspace clustering of hyperspectral images based on graph convolutional networks
High-dimensional and complex spectral structures make the clustering of hyperspectral
images (HSIs) a challenging task. Subspace clustering is an effective approach for …
images (HSIs) a challenging task. Subspace clustering is an effective approach for …
Transformer-based masked autoencoder with contrastive loss for hyperspectral image classification
X Cao, H Lin, S Guo, T Xiong… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In recent years, in order to solve the problem of lacking accurately labeled hyperspectral
image data, self-supervised learning has become an effective method for hyperspectral …
image data, self-supervised learning has become an effective method for hyperspectral …
Pseudo-Label-Based Unreliable Sample Learning for Semi-Supervised Hyperspectral Image Classification
H Yao, R Chen, W Chen, H Sun… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, pseudolabel-based deep learning methods have shown excellent performance in
semi-supervised hyperspectral image (HSI) classification. These methods usually select …
semi-supervised hyperspectral image (HSI) classification. These methods usually select …