Results 271 to 280 of about 15,264 (300)

SRF: SpectrumRecombineFormer for Hyperspectral Image Classification

ACM Transactions on Multimedia Computing, Communications, and Applications
Hyperspectral imaging is a valuable technique for accurately classifying materials because of the abundance of spectral information and high resolution it provides. However, the characteristics of Hyperspectral Imaging, such as high-dimensional features and information redundancy, pose significant challenges to data processing ...
Weipeng Jing 0001, Peilun Kang, Donglin Di, Juntao Gu, Linhui Li, Mahmoud Emam, Linda Mohaisen, Xun Yang 0001, Chao Li 0066   +8 more
openaire   +1 more source

Regularized methods for hyperspectral image classification

SPIE Proceedings, 2004
In this paper, we analyze regularized non-linear methods in the context of hyperspectral image classification. For this purpose, we compare regularized radial basis function neural networks (Reg-RBFNN), standard support vector machines (SVM), and kernel Fisher discriminant (KFD) analysis both theoretically and experimentally.
G. Camps Valls, Bruzzone, Lorenzo
openaire   +2 more sources

Collaborative learning for hyperspectral image classification

Neurocomputing, 2018
Abstract Recently, collaborative learning (CL) is introduced to combine active learning (AL) with semi-supervised learning (SSL), and solve the problem of limited training samples. In this paper, we proposed a novel CL framework for hyperspectral image classification, in which AL and SSL are collaboratively integrated using clustering (CLUC).
Chao Pan 0006, Jie Li 0001, Ying Wang 0007, Xinbo Gao 0001   +3 more
openaire   +1 more source

Segmentation as postprocessing for hyperspectral image classification

IEEE EUROCON 2015 - International Conference on Computer as a Tool (EUROCON), 2015
Hyperspectral imaging is a new technique in remote sensing that collects hundreds of images at differents wavelength values for the same area of the Earth. For instance the Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) sensor of NASA capable to obtain 224 spectral channels in a wavelength range between 40 and 250 nanometers. As a result each
Luis-Ignacio Jimenez, Antonio J. Plaza, Victor Andres Ayma, Pedro Achanccaray Diaz, Gilson A. O. P. da Costa, Raul Queiroz Feitosa   +5 more
openaire   +1 more source

Feature Mining for Hyperspectral Image Classification

Proceedings of the IEEE, 2013
Hyperspectral sensors record the reflectance from the Earth's surface over the full range of solar wavelengths with high spectral resolution. The resulting high-dimensional data contain rich information for a wide range of applications. However, for a specific application, not all the measurements are important and useful.
Xiuping Jia, Bor-Chen Kuo, Melba M. Crawford   +2 more
openaire   +1 more source

Efficient SpectralFormer for hyperspectral image classification

Digital Signal Processing, 2023
Weiliang Huang, Wenxuan He, Shuhong Liao, Zhen Xu 0001, Jingwen Yan   +4 more
openaire   +1 more source

Hyperspectral Image Transformer Classification Networks

IEEE Transactions on Geoscience and Remote Sensing, 2022
Xiaofei Yang 0002, Weijia Cao, Yao Lu 0008, Yicong Zhou   +3 more
openaire   +1 more source

Deep neural networks-based relevant latent representation learning for hyperspectral image classification

Pattern Recognition, 2022
Akrem Sellami, Salvatore Tabbone
exaly  

Hyperspectral Image Classification With Mamba

IEEE Transactions on Geoscience and Remote Sensing
Zhaojie Pan, Chenyu Li 0002, Antonio Plaza, Jocelyn Chanussot, Danfeng Hong   +4 more
openaire   +1 more source

An overview of hyperspectral image feature extraction, classification methods and the methods based on small samples

Applied Spectroscopy Reviews, 2023
Xueying Li, Zongmin Li, Pingping Fan
exaly