Results 71 to 80 of about 13,575,612 (179)

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, Ayush K. Sharma, Mario H. Andrade, Claudio C. Fernandes Filho, L. Felipe V. Ferrão, Aditya Singh, Anju Biswas, Charlie Messina, Esteban Rios   +8 more
wiley   +1 more source

Toward Content-Based Hyperspectral Remote Sensing Image Retrieval (CB-HRSIR): A Preliminary Study Based on Spectral Sensitivity Functions

Remote Sensing, 2019
With the emergence of huge volumes of high-resolution Hyperspectral Images (HSI) produced by different types of imaging sensors, analyzing and retrieving these images require effective image description and quantification techniques.
Olfa Ben-Ahmed, Thierry Urruty, Noël Richard, Christine Fernandez-Maloigne   +3 more
doaj   +1 more source

Hyperspectral image classification with convolutional neural networks [PDF]

, 2015
Hyperspectral image (HSI) classification is one of the most widely used methods for scene analysis from hyperspectral imagery. In the past, many different engineered features have been proposed for the HSI classification problem.
De Neve, Wesley, Viktor Slavkovikj, Sofie Van Hoecke, Steven Verstockt, Slavkovikj, Viktor, Van Hoecke, Sofie, Wesley De Neve, Van de Walle, Rik, Rik Van de Walle, Verstockt, Steven   +9 more
core   +1 more source

Spectral–spatial mamba adversarial defense network for hyperspectral image classification

International Journal of Digital Earth
Deep learning models have obtained great success in hyperspectral image classification tasks. Nevertheless, they are usually vulnerable to adversarial attacks. Some existing works have been made to defend against adversarial attacks in HSI classification.
Zhongqiang Zhang, Ye Wang, Dahua Gao, Haoyong Li, Guangming Shi   +4 more
doaj   +1 more source

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

Cytopathology, Volume 37, Issue 6, Page 587-602, November 2026.
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

Strategies for dimensionality reduction in hyperspectral remote sensing: A comprehensive overview

Egyptian Journal of Remote Sensing and Space Sciences
The technological advancements in spectroscopy give rise to acquiring data about different materials on earth's surface which can be utilized in a variety of potential applications.
Radhesyam Vaddi, B.L.N. Phaneendra Kumar, Prabukumar Manoharan, L. Agilandeeswari, V. Sangeetha   +4 more
doaj   +1 more source

Refinement of Hyperspectral Image Classification with Segment-Tree Filtering

Remote Sensing, 2017
This paper proposes a novel method of segment-tree filtering to improve the classification accuracy of hyperspectral image (HSI). Segment-tree filtering is a versatile method that incorporates spatial information and has been widely applied in image ...
Lu Li, Chengyi Wang, Jingbo Chen, Jianglin Ma   +3 more
doaj   +1 more source

Hybrid CNN-GCN Network for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, convolutional neural networks (CNNs) have been impressive due to their excellent feature representation abilities, but it is difficult to learn long-distance spatial structures information. Unlike CNN, graph convolutional networks (GCNs)
Cui-Ping Shi, Di-Ling Liao, Li-Guo Wang
semanticscholar   +1 more source

Dual-Branch Subpixel-Guided Network for Hyperspectral Image Classification [PDF]

IEEE Transactions on Geoscience and Remote Sensing
Deep learning (DL) has been widely applied to hyperspectral image (HSI) classification, owing to its promising feature learning and representation capabilities.
Zhu Han, Jin Yang, Lian-Ru Gao, Zhiqiang Zeng, Bing Zhang, Jocelyn Chanussot   +5 more
semanticscholar   +1 more source

Bespoke Real‐Time Multispectral Imaging for Apple Browning Evaluation Using Physics‐Informed Neural Networks

Journal of Food Process Engineering, Volume 49, Issue 11, November 2026.
A compact multispectral imaging system combined with a physics‐informed neural network enables real‐time quantitative monitoring and prediction of enzymatic browning in fresh‐cut apples. The Weibull‐constrained model improves temporal extrapolation over conventional Weibull and data‐driven neural network approaches.
Guojun Tang, Paul D. Teal, Alexander Doronin   +2 more
wiley   +1 more source