Results 201 to 210 of about 45,417 (317)

Sorting biotic and abiotic stresses on wild rocket by leaf-image hyperspectral data mining with an artificial intelligence model. [PDF]

Plant Methods, 2022
Navarro A, Nicastro N, Costa C, Pentangelo A, Cardarelli M, Ortenzi L, Pallottino F, Cardi T, Pane C.   +8 more
europepmc   +1 more source

A Geometric Simulator for the hyperspectral Mission EnMAP

, 2010
The hyperspectral satellite EnMAP (Environmental Mapping and Analysis Program) is scheduled to launch in 2014. It is a joint project by the GFZ (Deutsches GeoForschungsZentrum), the DLR (German Aerospace Center), Kayser-Threde and OHB-System.
Palubinskas, Gintautas, Makasy, Christine, Storch, Tobias, Schwind, Peter, Müller, Rupert   +4 more
core  

Multi‐Spectral Gaussian Splatting with Neural Color Representation

Computer Graphics Forum, EarlyView.
Abstract 3D Gaussian Splatting (3DGS) [KKLD23] has transformed novel‐view synthesis from RGB images, yet remains restricted to the visible spectrum. Many applications, including agricultural monitoring, rely on multi‐spectral imaging, where spectral camera alignment and scalability pose major challenges.
Lukas Meyer, Josef Grün, Maximilian Weiherer, Bernhard Egger, Marc Stamminger, Linus Franke   +5 more
wiley   +1 more source

Inverting the Concentrations of Chlorophyll-a and Chemical Oxygen Demand in Urban River Networks Using Normalized Hyperspectral Data. [PDF]

Sensors (Basel)
Guan R, Hou Y, Arif M, Xing Q.
europepmc   +1 more source

Hyperspectral data as a biodiversity screening tool can differentiate among diverse Neotropical fishes. [PDF]

Sci Rep, 2021
Kolmann MA, Kalacska M, Lucanus O, Sousa L, Wainwright D, Arroyo-Mora JP, Andrade MC.   +6 more
europepmc   +1 more source

What Are Computer‐Assisted Methods Achieving in Fine‐Needle Aspiration Cytology of the Pancreas? A Systematic Review and Meta‐Analysis

Cytopathology, EarlyView.
This meta‐analysis demonstrates high diagnostic accuracy of computer‐assisted methods in pancreatic EUS‐FNA cytology (AUC 0.92–0.96) and supports an integrated, cytopathologist‐led workflow in which artificial intelligence functions as an adjunct to diagnostic interpretation and on‐site evaluation (ROSE). Created in BioRender. Mohamed Mirzan, A. (2026)
Al‐Amaan Mohamed Mirzan, Roberto Dina
wiley   +1 more source

Integrating Hyperspectral Data and Deep Learning for Non-Destructive Prediction of Tea Quality Parameters Across Different Physical States of Tea Leaves and Growth Periods. [PDF]

Plants (Basel)
Zhou G, Ji H, Pan R, Yang X, Zhao S, Yang L, Shang X, Zhang H, Zhang H, Liu X, Ma Y, Zhu X, Jiang J, Fang W.   +13 more
europepmc   +1 more source

Principal component analysis of hyperspectral data for early detection of mould in cheeselets. [PDF]

Curr Res Food Sci, 2021
Farrugia J, Griffin S, Valdramidis VP, Camilleri K, Falzon O.   +4 more
europepmc   +1 more source

Differentiating solar lentigines from post‐inflammatory hyperpigmentation with hyperspectral imaging: A pilot study

International Journal of Cosmetic Science, EarlyView.
This preliminary study attempted to characterize solar lentigines and post‐inflammatory hyperpigmentation (PIH) observed on Japanese women. Colorimetric features and chromophore concentrations were measured using hyperspectral imaging for each hyperpigmentation type.
Victor Egana, Carl Blaksley, Ayako Itaya, Mai Edagawa, Alexandre Nicolas   +4 more
wiley   +1 more source

NDVI and Beyond: Vegetation Indices as Features for Crop Recognition and Segmentation in Hyperspectral Data. [PDF]

Sensors (Basel)
Nițu A, Florea C, Ivanovici M, Racoviteanu A.   +3 more
europepmc   +1 more source