Results 111 to 120 of about 107,679 (337)

Editorial for Special Issue “Hyperspectral Imaging and Applications”

Remote Sensing, 2019
Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging.
Chein-I Chang, Meiping Song, Junping Zhang, Chao-Cheng Wu   +3 more
doaj   +1 more source

Analyses of the Impact of Soil Conditions and Soil Degradation on Vegetation Vitality and Crop Productivity Based on Airborne Hyperspectral VNIR–SWIR–TIR Data in a Semi-Arid Rainfed Agricultural Area (Camarena, Central Spain) [PDF]

, 2022
Robert Milewski, Thomas Schmid, Sabine Chabrillat, Marcos Jiménez, Paula Escribano, M. Pelayo, Eyal Ben‐Dor   +6 more
openalex   +1 more source

Real‐time lithology identification while drilling based on drill cuttings image analysis with ensemble learning

Deep Underground Science and Engineering, EarlyView.
A lithology identification while drilling method was developed, integrating an automated cuttings sampling system, a smart drilling rig, and an ensemble learning model. Underground trials achieved 97.42% accuracy in real‐time identification of cuttings lithology and composition, enhancing hazard management and supporting unmanned drilling technology in
Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Xueqiu He, Liang Zhao   +7 more
wiley   +1 more source

Deep data: discovery and visualization Application to hyperspectral ALMA imagery [PDF]

, 2016
Erzsébet Merényi, Joshua P. Taylor, Andrea Isella   +2 more
openalex   +1 more source

Harnessing deep learning to quantify microstructural complexity in confocal images of plant protein gels

Food Biomacromolecules, EarlyView.
Abstract Understanding plant protein gel microstructure is key to designing functional food systems. This study introduces a deep learning framework using a U‐Net model with a ResNet34 encoder to segment and quantify confocal laser scanning microscopy (CLSM) images of plant protein gels.
Zhi Yang
wiley   +1 more source

Spectral Data-Driven Prediction of Soil Properties Using LSTM-CNN-Attention Model

Applied Sciences
Accurate prediction of soil properties is essential for sustainable land management and precision agriculture. This study presents an LSTM-CNN-Attention model that integrates temporal and spatial feature extraction with attention mechanisms to improve ...
Yiqiang Liu, Luming Shen, Xinghui Zhu, Yangfan Xie, Shaofang He   +4 more
doaj   +1 more source

Geostatistical Fusion of LiDAR and Hyperspectral Data to Improve the Spatial Prediction of Sand Content in a Forested Catchment of Southern Italy

, 2023
Annamaria Castrignanò, Gabriele Buttafuocò, Massimo Conforti, Mauro Maesano, Federico Valerio Moresi, Giuseppe Scarascia Mugnozza   +5 more
openalex   +2 more sources

Hyperspectral Imaging Combined With Image Fusion Features and Machine Learning to Discriminate Different Origins, Grades, and Shelf‐Life of Oranges

Food Safety and Health, EarlyView.
This study verified that it is feasible to distinguish oranges of different origins, grades and shelf lives by using hyperspectral technology. It covers spectral, image and graph technologies, as well as machine learning and deep learning models. ABSTRACT This study reports the first application of hyperspectral feature fusion technology combined with ...
Honghui Xiao, Hao Hu, Hanyi Mei, Hao Deng, Yongzhi Zhang, Jing Nie, Hao Wu, Karyne M. Rogers, Yuwei Yuan, Chunlin Li   +9 more
wiley   +1 more source

A Label‐Free Hyperspectral Imaging Device for Ex Vivo Characterization and Grading of Meningioma Tissues

Journal of Biophotonics, EarlyView.
HyperProbe1.1 enables rapid, label‐free biochemical mapping of freshly resected meningiomas. By quantifying endogenous biomarkers such as cytochrome c oxidase, hemoglobin derivatives, and lipids, the system reveals molecular signatures consistent with tumor grading and generates spatial maps that visualize metabolic and vascular heterogeneity across ...
Pietro Ricci, Camilla Bonaudo, Ivan Ezhov, Anam Toaha, Dorotea Nardini, Manuel Camelia, Federica Lucidi, Filippo Nozzoli, Tim Mach, Ilias Tachtsidis, Daniel Rueckert, Alessandro Della Puppa, Luca Giannoni, Francesco S. Pavone   +13 more
wiley   +1 more source

Deep Learning Integration in Optical Microscopy: Advancements and Applications

Microscopy Research and Technique, EarlyView.
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari, Sagnika Dutta, H. Deeksha, Samreen A. Patel, Budheswar Dehury, Nirmal Mazumder   +5 more
wiley   +1 more source