Results 21 to 30 of about 105,347 (307)
IEEE Access, 2020 Tree species diversity plays a significant role in our ecosystem. In order to monitor forest dynamics, hyperspectral remote sensing equipped on a small unmanned aerial vehicle (UAV) is commonly applied, such as individual tree detection and ...
Rui Yu +5 more
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A Hyperspectral Image Classification Method Using Multifeature Vectors and Optimized KELM
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 To improve the accuracy and generalization ability of hyperspectral image classification, a feature extraction method integrating principal component analysis (PCA) and local binary pattern (LBP) is developed for hyperspectral images in this article. The
Huayue Chen +4 more
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Remote Sensing, 2023 Neural network models for hyperspectral images classification are complex and therefore difficult to deploy directly onto mobile platforms. Neural network model compression methods can effectively optimize the storage space and inference time of the ...
Yu Lei +5 more
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A new kernel method for hyperspectral image feature extraction [PDF]
, 2017 Hyperspectral image provides abundant spectral information for remote discrimination of subtle differences in ground covers. However, the increasing spectral dimensions, as well as the information redundancy, make the analysis and interpretation of ...
Gao, Lianru +3 more
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TRANSFER LEARNING WITH LIMITED SAMPLES FOR THE SAME SOURCE HYPERSPECTRAL REMOTE SENSING IMAGES CLASSIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 A classification method for hyperspectral datasets with a limited number of samples based on transferred convolutional neural network (CNN) is proposed. For the CNN model, a lot of labeled samples are needed for the classification of hyperspectral images,
W. Li, Q. Liu, Y. Wang, H. Li
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Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image [PDF]
, 2013 Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or endmembers) with their corresponding proportions (or abundances). Endmember extraction
Benediktsson, Jon Atli +3 more
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Compressive Hyperspectral Imaging Using Progressive Total Variation [PDF]
, 2014 Compressed Sensing (CS) is suitable for remote acquisition of hyperspectral images for earth observation, since it could exploit the strong spatial and spectral correlations, llowing to simplify the architecture of the onboard sensors. Solutions proposed
Barducci, Alessandro +4 more
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In vivo hyperspectral imaging of skin malignant and benign tumors in visible spectrum
Journal of Biomedical Photonics & Engineering, 2018 The paper presents analysis of hyperspectral images for human skin cancer pathologies diagnostics. Hyperspectral images data contained backscattered spectra of normal skin and tumors. Analysis of hyperspectral images provided information about hemoglobin
Ivan A. Bratchenko +10 more
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High-resolution cathodoluminescence hyperspectral imaging of nitride nanostructures [PDF]
, 2012 Hyperspectral cathodoluminescence imaging provides spectrally and spatially resolved information on luminescent materials within a single dataset. Pushing the technique toward its ultimate nanoscale spatial limit, while at the same time spectrally ...
Chaowang Liu +9 more
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Target Detection System Design for Domestic Areas in Iran: Case Study in Abadan and Ahvaz, Using Satellite Multi-spectral Images of Landsat 8 and Sentinel 2 [PDF]
فناوری در مهندسی هوافضا, 2020 Hyperspectral images provide worthful spectral information for target detection. Since these images are not available in Iran, we use multi-spectral images with approximately 10 bands.
Maryam Imani
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