Results 21 to 30 of about 16,943 (161)
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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Multi-temporal Hyperspectral Anomaly Change Detection Based on Dual Space Conjugate Autoencoder [PDF]
Jisuanji kexue, 2023 Hyperspectral anomaly change detection can find anomaly changes from multi-temporal hyperspectral remote sensing images.These anomaly changes are rare,different from the overall background change trend,difficult to be found,but very intere-sting.For the ...
LI Shasha, XING Hongjie, LI Gang
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Volume Holographic Hyperspectral Imaging [PDF]
Applied Optics, 2004 A volume hologram has two degenerate Bragg-phase-matching dimensions and provides the capability of volume holographic imaging. We demonstrate two volume holographic imaging architectures and investigate their imaging resolution, aberration, and sensitivity.
Liu, W., Barbastathis, G., Psaltis, D.
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Remote Sensing Performance Enhancement in Hyperspectral Images
Sensors, 2018 Hyperspectral images with hundreds of spectral bands have been proven to yield high performance in material classification. However, despite intensive advancement in hardware, the spatial resolution is still somewhat low, as compared to that of color and
Chiman Kwan
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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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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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MORPHOLOGICAL SEGMENTATION OF HYPERSPECTRAL IMAGES
Image Analysis & Stereology, 2011 The present paper develops a general methodology for the morphological segmentation of hyperspectral images, i.e., with an important number of channels. This approach, based on watershed, is composed of a spectral classification to obtain the markers and a vectorial gradient which gives the spatial information. Several alternative gradients are adapted
Noyel, Guillaume +2 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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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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Smart Agricultural TechnologyThe accurate and effective monitoring of rice nitrogen status using hyperspectral datasets and estimation models is important for precision agriculture and intelligent breeding.
Zhonglin Wang +11 more
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