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Academic Articles & Research Papers
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Qingle Guo, Junping Zhang, Chongxiao Zhong, Ye Zhang • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2021)
With the increase in the availability of multitemporal hyperspectral images (HSIs), HSIs change detection (CD) methods, including pixel-level and subpixel-level based methods, have attracted great attention in recent years. However, the wid...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2021.3074538
Yuan Zi, Chenyu Zhou, Jiefu Chen, Zhu Han et al. • IEEE Access
(2025)
Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery to provide detailed insights into the Earthȁ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3597991
Yuchao Feng, Jianwei Zheng, Mengjie Qin, Cong Bai et al. • Remote Sensing
(2021)
Owing to the outstanding feature extraction capability, convolutional neural networks (CNNs) have been widely applied in hyperspectral image (HSI) classification problems and have achieved an impressive performance. However, it is well know...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13214407
Shiqi Feng, Xuquan Wang, Xiong Dun, Zhanshan Wang et al. • IEEE Photonics Journal
(2025)
Encoded computational hyperspectral cameras, propelled by advances in compressed sensing theory, making both miniaturization and real-time hyperspectral imaging feasible. Spectral-encoded or spatial-encoded hyperspectral imaging strategy ha...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JPHOT.2025.3624799
JongCheol Pyo, Hongtao Duan, Mayzonee Ligaray, Minjeong Kim et al. • Remote Sensing
(2020)
Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estim...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs12071073
Xiaofei Yang, Yunming Ye, Xutao Li, Raymond Y.K. Lau et al. • IEEE Transactions on Geoscience and Remote Sensing
(2018)
Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem. In contrast to conventional computer vision task...
OPENALEX
DOI: https://doi.org/10.1109/tgrs.2018.2815613
Hao Shi, Guo Cao, Youqiang Zhang, Zixian Ge et al. • Remote Sensing
(2022)
Deep learning (DL) has recently been a core ingredient in modern computer vision tasks, triggering a wave of revolutions in various fields. The hyperspectral image (HSI) classification task is no exception. A wide range of DL-based methods ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14174235
Shutao Li A, Weiwei Song, Leyuan Fang, Yushi Chen et al. • IEEE Transactions on Geoscience and Remote Sensing
(2019)
Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate classification of such data challenging for traditional machine ...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tgrs.2019.2907932
Emanuele Aiello, Mirko Agarla, Diego Valsesia, Paolo Napoletano et al. • IEEE Access
(2024)
Large-scale self-supervised pretraining of deep learning models is known to be critical in several fields, such as language processing, where its has led to significant breakthroughs. Indeed, it is often more impactful than architectural de...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3396990
Siyuan Liu, Yingchao Fan, Qi Hu, Bing Li et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2025)
Hyperspectral image (HSI) has more spectral information than conventional images, which helps to distinguish targets in a complex scene more accurately. However, HSI typically has a low spatial resolution, which limits their application sce...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2025.3586076