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Applications of hyperspectral imaging technology in the food industry
Emerging issues related to food quality include the need to ensure food safety, detect adulteration and enable traceability throughout the food...
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Hyperspectral retinal imaging biomarkers of ocular and systemic diseases
Hyperspectral imaging is a frontier in the field of medical imaging technology. It enables the simultaneous collection of spectroscopic and spatial...
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Quantum dot-enabled infrared hyperspectral imaging with single-pixel detection
Near-infrared (NIR) hyperspectral imaging is a powerful technique that enables the capture of three-dimensional (3D) spectra-spatial information...
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A compressive hyperspectral video imaging system using a single-pixel detector
Capturing fine spatial, spectral, and temporal information of the scene is highly desirable in many applications. However, recording data of such...
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Wide-field mid-infrared hyperspectral imaging beyond video rate
Mid-infrared hyperspectral imaging has become an indispensable tool to spatially resolve chemical information in a wide variety of samples. However,...
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Encoded Diffractive Optics for Hyperspectral Imaging
Recent hyperspectral imaging has been taking advantage of the development of diffractive optics elements (DOEs) to encode the spectral information in...
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Metasurface-empowered snapshot hyperspectral imaging with convex/deep (CODE) small-data learning theory
Hyperspectral imaging is vital for material identification but traditional systems are bulky, hindering the development of compact systems. While...
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Review of Three-Dimensional Reconstruction Based on Hyperspectral Imaging
In the past few decades, with the continuous progress in devices and research, both hyperspectral imaging technology and three-dimensional...
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Microsphere-assisted hyperspectral imaging: super-resolution, non-destructive metrology for semiconductor devices
As semiconductor devices shrink and their manufacturing processes advance, accurately measuring in-cell critical dimensions (CD) becomes increasingly...
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Quantitative measurement of internal quality of carrots using hyperspectral imaging and multivariate analysis
The study aimed to measure the carotenoid (Car) and pH contents of carrots using hyperspectral imaging. A total of 300 images were collected using a...
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Remote Sensing Techniques: Hyperspectral Imaging and Data Analysis
Hyperspectral imaging is a remote sensing technique that enables remote, noninvasive measurement of plant traits. Here, we outline the procedures for...
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Minimum Noise Fraction and Long Short-Term Memory Model for Hyperspectral Imaging
In recent years, deep learning techniques have presented a major role in hyperspectral image (HSI) classification. Most commonly Convolutional Neural...
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Early surveillance of rice bakanae disease using deep learning and hyperspectral imaging
Bakanae disease, caused by Fusarium fujikuroi , poses a significant threat to rice production and has been observed in most rice-growing regions. The...
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Hyperspectral imaging with machine learning for in vivo skin carcinoma margin assessment: a preliminary study
Surgical excision is the most effective treatment of skin carcinomas (basal cell carcinoma or squamous cell carcinoma). Preoperative assessment of...
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Retinal hyperspectral imaging in mouse models of Parkinson’s disease and healthy aging
Retinal hyperspectral imaging (HSI) is a non-invasive in vivo approach that has shown promise in Alzheimer’s disease. Parkinson’s disease is another...
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Wavelength and texture feature selection for hyperspectral imaging: a systematic literature review
Over the past two decades, hyperspectral imaging has become popular for non-destructive assessment of food quality, safety, and crop monitoring....
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Hyperspectral confocal imaging for high-throughput readout and analysis of bio-integrated microlasers
Integrating micro- and nanolasers into live cells, tissue cultures and small animals is an emerging and rapidly evolving technique that offers...
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Application of Hyperspectral Imaging to Identify Pine Seed Varieties
Seed variety purity is the main indicator of seed quality, which affects crop yield and product quality. In the present study, a new method for the...
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Semantic Segmentation of Hyperspectral Imaging Using Convolutional Neural Networks
Abstractusing neural networks in hyperspectral imaging helps to get through the obstruction to solving data analysis, classification, and...
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Hyperspectral imaging and pulse characterization
An advanced method for hyperspectral imaging was combined with phase retrieval and standard pulse characterization techniques to characterize...
