Aug 6, 2020 · We propose a novel siamese network, called the deep half-siamese network (Deep HSNet), for HU by fully considering diverse endmember properties.
Abstract—Over the past decades, numerous methods have been proposed to solve the linear or nonlinear mixing problems in hyperspectral unmixing (HU).
To this end, we propose a novel siamese network, called the deep half-siamese network (Deep HSNet), for HU by fully considering diverse endmember properties ...
Deep half-siamese networks for hyperspectral unmixing. GRSL 2020, Z. Han et al. [Paper]; Dual branch autoencoder network for spectral-spatial hyperspectral ...
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Deep half-siamese networks for hyperspectral unmixing. Z Han, D Hong, L Gao, B Zhang, J Chanussot. IEEE Geoscience and Remote Sensing Letters 18 (11), 1996-2000 ...
1 day ago · “Learning Interpretable Deep Disentangled Neural Networks for Hyperspectral Unmixing. ... “Deep Half-Siamese Networks for Hyperspectral Unmixing.” ...
Apr 24, 2024 · In recent years, deep learning and neural networks have become state-of-the-art for many tasks in machine learning and image processing.
Abstract—Linear spectral unmixing is an essential technique in hyperspectral image processing and interpretation. In recent years, deep learning-based ...
In this paper, an active learning-based siamese network (ALSN) is proposed to solve the limited labeled samples problem in HSI classification.
Missing: Half- Unmixing.
A 3D lightweight Siamese network (3DLSN) is proposed to solve the above problem. It does not only reduce the trainable parameter effectively but also requires ...
Missing: Half- Unmixing.