Results 91 to 100 of about 2,924,189 (218)
Hyperspectral images segmentation: a proposal [PDF]
, 2009 Hyper-Spectral Imaging (HIS) also known as chemical or spectroscopic imaging is an emerging technique that combines imaging and spectroscopy to capture both spectral and spatial information from an object. Hyperspectral images are made up of contiguous
GORETTA, Nathalie +8 more
core
HSI-IPGAN: Hyperspectral Image Inpainting via Generative Adversarial Network
, 2023 Abstract Due to the instability of the hyperspectral imaging system and the atmospheric interference, hyperspectral images (HSIs) often suffer from losing the image information of areas with different shapes, which significantly degrades the data quality and further limits the effectiveness of methods for subsequent tasks.
Hu Chen +4 more
openaire +1 more source
Genomic and phenomic prediction models improve selection accuracy for complex traits in alfalfa
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Predictive breeding has been proposed as an effective approach to accelerate genetic gain for complex traits. Genomic prediction (GP) models have been developed in alfalfa (Medicago sativa L.) for key traits in the last decade. More recently, phenomic prediction (PP) models have been proposed as a low‐cost, high‐throughput alternative to GP in
Pablo Sipowicz +8 more
wiley +1 more source
A Single Model CNN for Hyperspectral Image Denoising
, 2022 Denoising is a common preprocessing step prior to the analysis and interpretation of hyperspectral images (HSIs). However, the vast majority of methods typically adopted for HSI denoising exploit architectures originally developed for grayscale or RGB ...
Alessandro Maffei +5 more
core +1 more source
Development of a new spectral library classifier for airborne hyperspectral images on heterogeneous environments [PDF]
, 2011 The classification of hyperspectral images on heterogeneous environments without prior knowledge about the study area is a challenging task. Finding potential pure spectral signatures or endmembers (EM) of the various surface materials within an image is
Mende, Andre +4 more
core
Harnessing genetic variation for grain quality from diverse wheat landraces
New Phytologist, Volume 252, Issue 5, Page 1924-1942, December 2026.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
Quantifying soil ammonium and nitrite via soil gas emissions
Soil Science Society of America Journal, Volume 90, Issue 6, November/December 2026.Abstract Monitoring the soil mineral nitrogen (SMN) status of cropland is challenging due to large spatiotemporal variability. Here, we present a novel approach that correlates NH3, NO, and HONO emissions with SMN content, pH, and soil moisture, eliminating the need for destructive soil sampling. We conducted incubation experiments with five soils with
Matthias Claß, Nicolas Brüggemann
wiley +1 more source
Deep Fully Convolutional Embedding Networks for Hyperspectral Images Dimensionality Reduction
, 2021 Due to the superior spatial–spectral extraction capability of the convolutional neural network (CNN), CNN shows great potential in dimensionality reduction (DR) of hyperspectral images (HSIs).
Maoguo Gong +5 more
core +1 more source
Scalable Room‐Temperature Terahertz Graphene Cameras
Small Methods, Volume 10, Issue 21, 9 November 2026.ABSTRACT Terahertz (THz) imaging has emerged as a powerful tool for non‐destructive, label‐free analysis across several scientific disciplines, ranging from materials science to biomedical research. By capturing the spatial‐dependent information in a broad range of frequencies, this technique enables the identification of chemical composition ...
Lili Shi +2 more
wiley +1 more source