Results 11 to 20 of about 18,058 (162)
Hyperspectral Imaging for Bloodstain Identification [PDF]
Sensors, 2021 Blood is key evidence to reconstruct crime scenes in forensic sciences. Blood identification can help to confirm a suspect, and for that reason, several chemical methods are used to reconstruct the crime scene however, these methods can affect subsequent DNA analysis. Therefore, this study presents a non-destructive method for bloodstain identification
Maheen Zulfiqar +4 more
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HYPERSPECTRAL PANORAMIC IMAGING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 Abstract. Hyperspectral instruments are designed for the characterisation of planetary surfaces, oceans and the atmosphere. At the moment there are a number of aircraft systems and planned space missions. Examples for this are the hyperspectral missions for Earth remote sensing (EnMAP) and also for deep space and planetary missions (Mercury mission ...
Müller-Rowold, Malte, Reulke, Ralf
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Nature Reviews Methods PrimersHyperspectral imaging (HSI) is an advanced sensing modality that simultaneously captures spatial and spectral information, enabling non-invasive, label-free analysis of material, chemical, and biological properties. This Primer presents a comprehensive overview of HSI, from the underlying physical principles and sensor architectures to key steps in ...
Danfeng Hong +8 more
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VGC 2023 - Unveiling the dynamic Earth with digital methods : 5th Virtual Geoscience Conference ; Book of Abstracts, 2023 Hyperspectral imaging (HSI) technology is a combination of conventional imaging and spectroscopic techniques, which has a unique ability to simultaneously acquire both the spatial and spectral data of a specimen. The HSI is a novel optical tool in food processing that has a great potential for rapidly identifying bacteria (and possibly other ...
Lorenz, Sandra, Kirsch, Moritz
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The Future of Hyperspectral Imaging [PDF]
Journal of Imaging, 2019 The Special Issue on hyperspectral imaging (HSI), entitled “The Future of Hyperspectral Imaging”, has published 12 papers. Nine papers are related to specific current research and three more are review contributions: In both cases, the request is to propose those methods or instruments so as to show the future trends of HSI.
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Tongue Coating Grading Identification Using Deep Learning for Hyperspectral Imaging Data
IEEE Access, 2023 Tongue diagnosis is one of the four diagnostic methods of traditional Chinese medicine (TCM), which has important value in clinical disease diagnosis and efficacy evaluation.
Dong Zhang +4 more
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Deep Pansharpening via 3D Spectral Super-Resolution Network and Discrepancy-Based Gradient Transfer
Remote Sensing, 2022 High-resolution (HR) multispectral (MS) images contain sharper detail and structure compared to the ground truth high-resolution hyperspectral (HS) images. In this paper, we propose a novel supervised learning method, which considers pansharpening as the
Haonan Su, Haiyan Jin, Ce Sun
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HIDSAG: Hyperspectral Image Database for Supervised Analysis in Geometallurgy
Scientific Data, 2023 Supervised analysis using spectral data requires a well-informed characterisation of the response variables and abundant spectral data points. The presented hyperspectral dataset comes from five sets of geometallurgical samples, each characterised by ...
Alejandro Ehrenfeld +6 more
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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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