Results 111 to 120 of about 9,650 (249)

Deep Learning for hyperspectral Image Classification.

, 2021
Hyperspectral Imaging (HSI) has been extensively utilized in many real-life applications because it benefits from the detailed spectral information contained in each pixel. Notably, the complex characteristics i.e., the nonlinear relation among the captured spectral information and the corresponding object of HSI data make accurate classification ...
openaire   +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

When biology meets materials science – Interdisciplinary applications of electron microscopy

Journal of Microscopy, EarlyView.
Abstract Research at the interface between biology and materials science creates challenges for electron microscopists. Everything from the sample preparation to the choice of imaging and analytical techniques and the interpretation of the resulting data refuses to sit comfortably within the domain of one discipline or the other.
Martin Saunders, Peta L. Clode, Enoch V. S. Wong, Anna‐Lee Jessop, Gerd E. Shröder‐Turk, Felix de Tombeur   +5 more
wiley   +1 more source

Evaluating maturity of organic matter in hydrated C1 and CM‐like clasts and a dehydrated clast within a polymict eucrite and a howardite

Meteoritics &Planetary Science, EarlyView.
Abstract Volatile‐rich xenolithic clasts in different types of brecciated meteorites represent unique pristine solar system material. This study investigates the maturity and thermal history of organic matter using Raman spectroscopy and aqueous alteration effects using infrared spectroscopy in the matrix of 15 volatile‐rich clasts (C1 and CM‐like ...
Swarna Prava Das, Alessandro Maturilli, Aurélie Van den Neucker, Markus Patzek, Dipak Kumar Panda, Gopal K. Pradhan, Guneshwar Thangjam, Surya Snata Rout   +7 more
wiley   +1 more source

Hyperspectral Image Classification

, 2020
Rajesh Gogineni, Ashvini Chaturvedi
openaire   +2 more sources

A novel method based on high‐resolution imaging spectroscopy to predict fine‐root traits and the economics space of fresh tree roots

New Phytologist, EarlyView.
Maps of the estimated root nitrogen concentration in the < 0.5‐mm‐diameter classes of 20 woody species based on the imaging spectroscopy using the shortwave infrared spectral region. Summary Tree fine‐root morphological, anatomical, and chemical traits are important to reflect belowground resource acquisition strategies to support tree growth, but ...
Naoki Makita, Natsuko Tanikawa, Tatsuro Nakaji   +2 more
wiley   +1 more source

A Computer Vision‐Based Methodology to Estimate Fruit Colour Diversity in Ornamental Pepper (Capsicum spp.)

Plant Breeding, EarlyView.
ABSTRACT Fruit colour diversity within different ripening stages confers ornamental value for pepper plants. Using images can be helpful in analysing the fruit colour‐related genetic diversity and enable selecting accessions for ornamental purposes by avoiding subjectiveness.
Marcos Bruno da Costa Santos, Raylson de Sá Melo, Victor Eduardo de Carvalho Sousa, Artur Mendes Medeiros, Angela Maria dos Santos Pessoa, Silvokleio da Costa Silva, Antonia Maiara Marques do Nascimento, Priscila Alves Barroso   +7 more
wiley   +1 more source

Enhancing Predictive Ability of Agronomic and Quality Traits in Ethiopian Malting Barley (Hordeum vulgare L.) Using Spectral Variable Selection Methods

Plant Breeding, EarlyView.
ABSTRACT Phenomic selection (PS) offers a cost‐effective, breeder‐friendly approach for public breeding programmes with limited access to genotyping or restricted financial resources for laboratory infrastructure. Since PS relies on high‐throughput phenotyping data, which is often derived from near‐infrared spectroscopy (NIRS) of harvested seeds ...
Tigist Tadesse, Peer Wilde, Wondimu Ejerso, Dorothea Borchardt, Patrick Thorwarth, Thomas Miedaner   +5 more
wiley   +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, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Phenotypic scoring of canola blackleg severity using machine learning image analysis

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Canola blackleg is a fungal disease that causes significant yield loss and plant death of infected canola (Brassica napus L., Brassica rapa L., Brassica juncea L.) fields worldwide. One of the most effective methods for controlling blackleg is through the cultivation of resistant varieties.
Qiao Hu, Sarah Anderson, Stuart Gardner, Thomas W. Ernst, Chadwick B. Koscielny, Navratan S. Bahia, Charles G. Johnson Jr, Andrew C. Jarvis, Joseph S. Hynek, Nathan Coles, Igor Falak, David R. Charne, Manuel E. Ruidiaz, Julien Linares, Anastasios Mazis, Daniel J. Stanton   +15 more
wiley   +1 more source