Results 71 to 80 of about 2,627,069 (171)
Quality criteria benchmark for hyperspectral imagery [PDF]
, 2005 Hyperspectral data appear to be of a growing interest over the past few years. However, applications for hyperspectral data are still in their infancy as handling the significant size of the data presents a challenge for the user community.
Christophe, Emmanuel +2 more
core +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 +12 more
wiley +1 more source
Multifiltering MLP for Spectral Super-Resolution With Remote Sensing Image Verification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingSpectral super-resolution (SSR) has become an attractive approach to reconstructing hyperspectral images (HSIs) from more available RGB images or multispectral images owing to the powerful representation capability of deep learning.
Gong Li +4 more
doaj +1 more source
The Plant Phenome Journal, Volume 9, Issue 1, December 2026.Abstract Evaluating physiological maturity is an important trait in dry bean breeding (Phaseolus vulgaris L.), but field scoring can be inaccurate, subjective, and a persistent bottleneck in multi‐environment trials. To address this, we developed a low‐cost, high‐throughput pipeline that predicts plot‐level days after planting at maturity from time ...
Aliasghar Bazrafkan +4 more
wiley +1 more source
Models and Methods for Automated Background Density Estimation in Hyperspectral Anomaly Detection [PDF]
, 2012 Detecting targets with unknown spectral signatures in hyperspectral imagery has been proven to be a topic of great interest in several applications. Because no knowledge about the targets of interest is assumed, this task is performed by searching the ...
VERACINI, TIZIANA
core
eFood, Volume 7, Issue 5, October 2026.Portable NIRS combined with machine learning enabled rapid and accurate authentication of cattle and buffalo meat. Optimized models (XGBoost, CNN) achieved > 98% accuracy, while SHAP revealed key spectral regions. This dual approach offers a field‐ready, reagent‐free tool for fraud prevention and traceability. ABSTRACT Ensuring the authenticity of high‐
Dip Ghosh, Raad Al Deen, Md. Abul Hashem
wiley +1 more source
Journal of Food Safety, Volume 46, Issue 5, October 2026.Hyperspectral imaging and an optimized stacking ensemble learning model are developed for rapid, nondestructive toxicological assessment of fish meat. This framework integrated multiple machine learning classifiers to accurately distinguish toxicologically contaminated fish from fresh samples using both reduced (25‐band) and full (224‐band) spectral ...
Muhammad Aqeel +5 more
wiley +1 more source
Hyperspectral colon tissue cell classification [PDF]
, 2004 A novel algorithm to discriminate between normal and malignant tissue cells of the human colon is presented. The microscopic level images of human colon tissue cells were acquired using hyperspectral imaging technology at contiguous wavelength intervals ...
Rajpoot, Nasir M. (Nasir Mahmood) +2 more
core
Classification techniques for hyperspectral remote sensing [PDF]
, 2011 This study concerns with classification techniques in high dimensional space such as that of Hyperspectral Imaging (HSI) data sets, with objectives of understanding the strength and weakness of various classifiers and at the same time to study how ...
Kam, Firmin
core +4 more sources