In this paper, a semi-supervised CRF(ssCRF) is proposed for hyperspectral image classification with limited labeled pixels. Laplacian Support Vector Machine( ...
ABSTRACT. Conditional Random Field(CRF) has been successfully ap- plied to the hyperspectral image classification. However, it.
ABSTRACT. Remotely sensed hyperspectral imaging allows for the detailed anal- ysis of the surface of the Earth using advanced imaging instruments.
In this work, we develop a new semi-supervised discriminative random field (DRF) technique for spatial-spectral classification of hyperspectral images, which ...
Dec 12, 2023 · We propose a novel semisupervised algorithm for HSI classification by introducing spectral angle distance (SAD) as a loss function and employing multilayer ...
Hyperspectral remote sensing image classification is important aspect of current research. Extreme learning machine (ELM) has been widely used in the field of ...
In this paper we employ the graphs constructed with a typical manifold learning method-locally linear embedding (LLE), based on which semi-supervised ...
Missing: Conditional | Show results with:Conditional
This paper proposes a novel semi-supervised hyperspectral image classification framework which utilizes self-training to gradually assign highly confident ...
Missing: Conditional | Show results with:Conditional
This review paper presents various semi-supervised techniques used for hyperspectral image classification and research challenges are identified from ...
People also ask
What is hyperspectral classification in remote sensing?
What is supervised image classification in remote sensing?
Which neural networks for hyperspectral classification?
What is remote sensing image classification?
Oct 29, 2021 · In this work, we develop a new semisupervised discriminative random field (DRF) technique for spatial-spectral classification of hyperspectral ...