Aug 11, 2021 · The experimental results validated that the classification accuracy and robustness of ALPN significant exceeded the comparison baselines.
Dec 31, 2021 · The experimental results validated that the classification accuracy and robustness of ALPN significant exceeded the comparison baselines.
Jul 28, 2021 · With the blossom of deep learning, many excellent deep learning methods are proposed for hyperspectral imagery classification, such as HybridSN ...
Dec 9, 2024 · ALPN [23] proposed an active-learning-based few-shot hyperspectral imagery classification method to gradually increase labeled instances using a ...
Dec 12, 2024 · Reports from Zhejiang University Provide New Insights into Geoscience (Alpn: Active-learning-based Prototypical Network for Few-shot ...
ALPN: Active-learning-based prototypical network for few-shot hyperspectral imagery classification. X Li, Z Cao, L Zhao, J Jiang. IEEE Geoscience and Remote ...
ALPN: Active-Learning-Based Prototypical Network for Few-Shot Hyperspectral Imagery Classification[J]. IEEE Geoscience and Remote Sensing Letters, 2021, 19 ...
Dec 9, 2024 · In this paper, an active learning-based siamese network (ALSN) is proposed to solve the limited labeled samples problem in HSI classification.
A large number of experimental results show that the proposed AL-MRIS method can achieve excellent classification performance with few-shot training samples, ...
Tensor-Based Few-Shot Learning for Cross-Domain Hyperspectral Image ...
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In this paper, we attempt to use tensor mathematics for modeling the HSI and propose a novel few-shot learning method, called tensor-based few-shot Learning ( ...