Results 71 to 80 of about 8,883 (219)

High Performance Computing for Hyperspectral Remote Sensing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2011
Advances in sensor and computer technology are revolutionizing the way remotely sensed data is collected, managed and analyzed. In particular, many current and future applications of remote sensing in Earth science, space science, and soon in exploration science will require real- or near real-time processing capabilities.
Antonio Plaza, Qian Du 0001, Yang-Lang Chang, Roger L. King   +3 more
openaire   +1 more source

Spectral response of guava leaves under infestation by Costalimaita ferruginea (coleoptera: Chrysomelidae)

Agricultural and Forest Entomology, EarlyView.
Coccinellidae (Coleoptera), Miridae (Hemiptera), Hemerobiidae (Neuroptera), Pentatomidae (Hemiptera), Anystidae (Acari), Erythraeidae (Acari) and spiders (Araneidae, Oxyopidae and Salticidae) fed on the invasive paropsine leaf beetles in Marlborough, New Zealand.
Souradji I. Bachirou, Pedro G. Peixoto, David L. Rosalen   +2 more
wiley   +1 more source

A Tool for Analysis of Spectral Indices for Remote Sensing of Vegetation and Crops Using Hyperspectral Images

Entre Ciencia e Ingeniería, 2019
Food requirements in the world have increased, evidencing the necessity to improve standard techniques of agricultural production. To do so, one option is through technological elements like hyperspectral remote sensing of vegetation and crops.
David Ruiz Hidalgo, Bladimir Bacca Cortés, Eduardo Caicedo Bravo   +2 more
doaj   +1 more source

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

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

Breeding 5.0: Artificial intelligence (AI)‐decoded germplasm for accelerated crop innovation

Journal of Integrative Plant Biology, EarlyView.
ABSTRACT Crop breeding technologies are vital for global food security. While traditional methods have improved yield, stress tolerance, and nutrition, rising challenges such as climate instability, land loss, and pest pressure now demand new solutions.
Jiayi Fu, Shouzhi Zheng, Longjiang Fan, Xiaoming Zheng, Qian Qian   +4 more
wiley   +1 more source

Brain tissue classification in hyperspectral images using multistage diffusion features and transformer

Journal of Microscopy, EarlyView.
Abstract Brain surgery is a widely practised and effective treatment for brain tumours, but accurately identifying and classifying tumour boundaries is crucial to maximise resection and avoid neurological complications. This precision in classification is essential for guiding surgical decisions and subsequent treatment planning.
Neetu Sigger, Tuan T. Nguyen, Gianluca Tozzi   +2 more
wiley   +1 more source

Bridging data silos to holistically model plant macrophenology

New Phytologist, EarlyView.
Summary Phenological response to global climate change can impact ecosystem functions. There are various data sources from which spatiotemporal and taxonomic phenological data may be obtained: mobilized herbaria, community science initiatives, observatory networks, and remote sensing.
Lizbeth G. Amador, Tadeo H. Ramirez‐Parada, Isaac W. Park, Susan J. Mazer, Aaron M. Ellison, Margaret O'Brien, Eric R. Sokol, Colin A. Smith, Charles C. Davis, Sydne Record   +9 more
wiley   +1 more source

A short survey of hyperspectral remote sensing applications in agriculture

2013 6th International Conference on Recent Advances in Space Technologies (RAST), 2013
Hyperspectral sensors are devices that acquire images over hundreds of spectral bands, thereby enabling the extraction of spectral signatures for objects or materials observed. Hyperspectral remote sensing has been used over a wide range of applications, such as agriculture, forestry, geology, ecological monitoring and disaster monitoring.
Teke, Mustafa, Deveci, Husne Seda, Haliloglu, Onur, Gurbuz, Sevgi Zubeyde, Sakarya, Ufuk   +4 more
openaire   +4 more sources

Using reflectance spectra and Pl@ntNet to identify herbarium specimens: a case study with Lithocarpus

New Phytologist, EarlyView.
Summary The digitisation of plant collections is bringing large quantities of information into accessible electronic databases. However, in recent decades, traditional taxonomic work in collections has declined, meaning that more specimens are only determined to family or genus, particularly when lacking key identification structures.
Barbara M. Neto‐Bradley, Pierre Bonnet, Hervé Goëau, Alexis Joly, Jeannine Cavender‐Bares, David A. Coomes   +5 more
wiley   +1 more source