Results 11 to 20 of about 4,082 (191)
Improved Transformer Net for Hyperspectral Image Classification
Remote Sensing, 2021 In recent years, deep learning has been successfully applied to hyperspectral image classification (HSI) problems, with several convolutional neural network (CNN) based models achieving an appealing classification performance.
Yuhao Qing +3 more
doaj +4 more sources
When Lie Groups Meet Hyperspectral Images: Equivariant Manifold Network for Few-Shot HSI Classification. [PDF]
Sensors (Basel)Hyperspectral imagery (HSI) offers rich spectral signatures and fine-grained spatial structures for remote sensing, but practical HSI classification is often constrained by scarce labels and complex geometric disturbances, including translation, rotation, scaling, and shear.
Ban H +7 more
europepmc +4 more sources
mHC-HSI: Clustering-Guided Hyper-Connection Mamba for Hyperspectral Image Classification [PDF]
CoRRRecently, DeepSeek has invented the manifold-constrained hyper-connection (mHC) approach which has demonstrated significant improvements over the traditional residual connection in deep learning models \cite{xie2026mhc}. Nevertheless, this approach has not been tailor-designed for improving hyperspectral image (HSI) classification.
Yimin Zhu 0002 +8 more
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Diseases of the Esophagus, 2022 Abstract Background and aim Digital pathology will revolutionize the discriminate of malignant and non-malignant cells in histologically specimens. Hyperspectral imaging (HSI), a new technology combing imaging with spectroscopy might be beneficial for tumor cell identification.
M Maktabi +6 more
openaire +2 more sources
Diseases of the Esophagus, 2022 Abstract Hyperspectral imaging (HSI), as recently applied in medicine, is a novel technology combining imaging with spectroscopy. It might be used to identify, classify and discriminate malignant and non-malignant cells of histopathologic specimens.
Marianne Maktabi +6 more
openaire +2 more sources
Remote Sensing, 2019 Hyperspectral image (HSI) classification is one of the most active topics in remote sensing. However, it is still a nontrivial task to classify the hyperspectral data accurately, since HSI always suffers from a large number of noise pixels, the ...
Fuding Xie +3 more
doaj +2 more sources
O129 CLASSIFICATION OF BARRETT’S CARCINOMA SPECIMENS BY HYPERSPECTRAL IMAGING (HSI)
Diseases of the Esophagus, 2019 Abstract Aim Hyperspectral imaging (HSI) technology combines imaging with spectroscopy and can be used for the classification of malignant and non-malignant cells. Thereby HSI combined with artificial intelligent algorithms can be used to predict tumor cells in in Barrett’s carcinoma specimens.
Thieme René +5 more
openaire +2 more sources
Remote Sensing, 2020 Hyperspectral image (HSI) classification has become one of the most significant tasks in the field of hyperspectral analysis. However, classifying each pixel in HSI accurately is challenging due to the curse of dimensionality and limited training samples.
Yunhao Zou +3 more
doaj +2 more sources
Contrastive Learning Based on Transformer for Hyperspectral Image Classification
Applied Sciences, 2021 Recently, deep learning has achieved breakthroughs in hyperspectral image (HSI) classification. Deep-learning-based classifiers require a large number of labeled samples for training to provide excellent performance.
Xiang Hu +4 more
doaj +2 more sources
A Novel Analysis Dictionary Learning Model Based Hyperspectral Image Classification Method
Remote Sensing, 2019 Supervised hyperspectral image (HSI) classification has been acknowledged as one of the fundamental tasks of hyperspectral data analysis. Witnessing the success of analysis dictionary learning (ADL)-based method in recent years, we propose an ADL-based ...
Wei Wei +5 more
doaj +2 more sources