Results 81 to 90 of about 11,517,403 (217)
HyperGAN: A Hyperspectral Image Fusion Approach Based on Generative Adversarial Networks
Remote SensingThe objective of hyperspectral pansharpening is to fuse low-resolution hyperspectral images (LR-HSI) with corresponding panchromatic (PAN) images to generate high-resolution hyperspectral images (HR-HSI).
Jing Wang +6 more
doaj +1 more source
Hyperspectral image classification with convolutional neural networks [PDF]
, 2015 Hyperspectral image (HSI) classification is one of the most widely used methods for scene analysis from hyperspectral imagery. In the past, many different engineered features have been proposed for the HSI classification problem.
De Neve, Wesley +9 more
core +1 more source
Harnessing genetic variation for grain quality from diverse wheat landraces
New Phytologist, EarlyView.Grain protein content is usually measured on bulk samples, hiding variation between individual grains. We used hyperspectral imaging to predict protein in c. 15 000 single grains from over 500 Watkins wheat landraces grown in two environments, resolving both mean protein content and grain‐to‐grain uniformity.
Luqman B. Safdar +15 more
wiley +1 more source
Periodontology 2000, EarlyView.Abstract Background Artificial intelligence (AI) is increasingly gaining attention in the field of periodontology and implant dentistry. Currently developed models can support diagnosis, treatment planning, and maintenance monitoring. However, most of the available literature is based on retrospective and often single‐modality data sets.
Aminollah Khormali +2 more
wiley +1 more source
Research progress on anomaly target detection algorithms for hyperspectral imagery
Geocarto InternationalHyperspectral image (HSI) data plays an important role in remote sensing images, and researchers have done a great deal of work to understand and recognize HSI.
Baozhi Cheng, Yan Gao
doaj +1 more source
Learning a Model-Based Deep Hyperspectral Denoiser from a Single Noisy Hyperspectral Image
, 2021 Hyperspectral image (HSI) denoising is a crucial preprocessing procedure to improve the quality of HSI. Model-based methods take the degradation model and the structure of underlying clean HSI into account for denoising but require a large number of ...
Shuyin Tao +11 more
core +1 more source
Hyperspectral Imaging (HSI) of Human Kidney Allografts
, 2021 Zusammenfassung der Arbeit /Dissertation zur Erlangung des akademischen Grades Dr. med. Hyperspectral Imaging (HSI) of Human Kidney Allografts Die HSI Bildgebung ist ein nichtinvasives Instrument zur quantitativen Bewertung der Sauerstoffanreicherung parenchymatöser Organe, der Mikroperfusion von Transplantaten sowie zur Messung der Hämoglobin- und ...
openaire +1 more source
Land use/land cover (LULC) classification using hyperspectral images: a review
Geo-spatial Information ScienceIn the rapidly evolving realm of remote sensing technology, the classification of Hyperspectral Images (HSIs) is a pivotal yet formidable task. Hindered by inherent limitations in hyperspectral imaging, enhancing the accuracy and efficiency of HSI ...
Chen Lou +6 more
doaj +1 more source
Local Low-Rank and Sparse Representation for Hyperspectral Image Denoising
IEEE Access, 2019 Hyperspectral image (HSI) denoising is a fundamental task in a plethora of HSI applications. Global low-rank property is widely adopted to exploit the spectral-spatial information of HSIs, providing satisfactory denoising results.
Guanqun Ma +3 more
doaj +1 more source
Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang +12 more
wiley +1 more source