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Longqian Huang, Ruichen Luo, Xü Liu, Xiang Hao • Light Science & Applications
(2022)
The goal of spectral imaging is to capture the spectral signature of a target. Traditional scanning method for spectral imaging suffers from large system volume and low image acquisition speed for large scenes. In contrast, computational sp...
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DOI: https://doi.org/10.1038/s41377-022-00743-6
PMC: 8927154
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
Shiyao Duan, Jiaojiao Li, Rui Song, Yunsong Li et al. • Remote Sensing
(2023)
Deep learning networks based on CNNs or transformers have made progress in spectral reconstruction (SR). However, many methods focus solely on feature extraction, overlooking the interpretability of network design. Additionally, models excl...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs15102619