Results 81 to 90 of about 6,341 (223)
Approaches for Hyperspectral Image Classification Detailed Review
, 2021 Hyperspectral Image (HSI) processing is the new advancement in image / signal processing field. The growth over the years is appreciable. The main reason behind the successful growth of the Hyperspectral imaging field is due to the enormous amount of ...
Beena R. Shetty +2 more
core +1 more source
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
New Zealand Journal of Crop and Horticultural Science, Volume 54, Issue 2, June 2026.Water loss is a key factor affecting the postharvest quality and shelf life of blueberries, and storage conditions (humidity and time) play an important role in regulating water retention capacity of stored berries. This study aims to explore the variation of moisture content (MC) in blueberries under different storage humidity and storage time ...
RunKai Wang +3 more
wiley +1 more source
Double-Branch Multi-Attention Mechanism Network for Hyperspectral Image Classification
, 2019 Recently, Hyperspectral Image (HSI) classification has gradually been getting attention from more and more researchers. HSI has abundant spectral and spatial information; thus, how to fuse these two types of information is still a problem worth studying.
Qifan Yang +4 more
core +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
An Efficient Graph Convolutional RVFL Network for Hyperspectral Image Classification
, 2023 Graph convolutional networks (GCN) have emerged as a powerful alternative tool for analyzing hyperspectral images (HSIs). Despite their impressive performance, current works strive to make GCN more sophisticated through either elaborate architecture or ...
Min Zhang +4 more
core +1 more source
Multimodal Assessment of Kidney Quality During 24‐h of Normothermic Machine Perfusion
Artificial Organs, Volume 50, Issue 6, Page 851-865, June 2026.Normothermic machine perfusion (NMP) has emerged as a promising tool for assessing kidney quality prior to transplantation; however, reliable biomarkers remain to be established. In this study, thirteen porcine kidneys were perfused for 24 h using an autologous leukocyte‐filtered whole blood‐based perfusate applying urine recirculation.
Marlene Pühringer +22 more
wiley +1 more source
Geophysical Research Letters, Volume 53, Issue 9, 16 May 2026.Abstract The Arctic warms faster than anywhere else on Earth, and paleoclimate data are key to placing this amplified response in a long‐term context. But most past temperature proxies record growing season conditions, when their biological signal carriers are produced.
Willem G. M. van der Bilt +8 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
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