Results 101 to 110 of about 11,517,403 (217)
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 +2 more
wiley +1 more source
Double-Branch Multi-Attention Mechanism Network for Hyperspectral Image Classification
, 2019 Recently, Hyperspectral Image (HSI) classification has gradually been getting attention from more and more researchers. HSI has abundant spectral and spatial information; thus, how to fuse these two types of information is still a problem worth studying.
Qifan Yang +4 more
core +1 more source
Deep Parameterized Neural Networks for Hyperspectral Image Denoising
, 2023 Sparse representation (SR)-based hyperspectral image (HSI) denoising methods normally average the local denoising results of multiple overlapped cubes to recover the whole HSI.
Jiantao Zhou +8 more
core +1 more source
Seeing the unseen: hyperspectral imaging opens a new window into the root economics space
New Phytologist, EarlyView.
Boris Rewald
wiley +1 more source
New Primary and Secondary Prevention Measures for Cutaneous Melanoma: A Systematic Review
Cancer Reports, Volume 9, Issue 10, October 2026.ABSTRACT Background Cutaneous melanoma is the deadliest type of skin cancer, with increasing incidence and mortality rates. Therefore, primary and secondary prevention are of utmost importance. Claims The objective is to evaluate new recent evidence on primary and secondary prevention strategies for cutaneous melanoma.
Maria Palau–del–Valle +2 more
wiley +1 more source
Hyperspectral Denoising Using Asymmetric Noise Modeling Deep Image Prior
, 2023 Deep image prior (DIP) is a powerful technique for image restoration that leverages an untrained network as a handcrafted prior. DIP can also be used for hyperspectral image (HSI) denoising tasks and has achieved impressive performance.
Xiangyong Cao +5 more
core +1 more source
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
Multiscale Hyperspectral Pansharpening Network Based on Dual Pyramid and Transformer
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral pansharpening is to fuse a high spatial resolution panchromatic image (PAN) with a low spatial resolution hyperspectral image (LR-HSI) and generate high resolution hyperspectral image (HR-HSI).
Hengyou Wang, Jie Zhang, Lian-Zhi Huo
doaj +1 more source
Multi-Scale CNN Based Garbage Detection of Airborne Hyperspectral Data
IEEE Access, 2019 Garbage detection is important for environmental monitoring in large areas. However, the manual patrol is time-consuming and labor-intensive. This paper proposes a method for monitoring garbage distribution in large areas with airborne hyperspectral data.
Dan Zeng +3 more
doaj +1 more source
Food Science &Nutrition, Volume 14, Issue 10, October 2026.Meat freshness monitoring is illustrated as an integrated system that links spoilage mechanisms to advanced detection and digital technologies. Microbial activity, enzymatic degradation, and chemical oxidation generate measurable changes in meat quality.
Md Abu Rayhan +4 more
wiley +1 more source