Results 91 to 100 of about 23,100 (259)

Cutting Through the Green: A Case for Grassland Archaeology Using UAV Multispectral Data

Archaeological Prospection, EarlyView.
ABSTRACT Advances in low‐altitude remote sensing are needed to improve the effectiveness of archaeological prospection in the Netherlands. The geomorphological situation and land use history make applying various remote sensing and geophysical technologies particularly challenging.
Roeland Emaus
wiley   +1 more source

Self-Supervised Deep Multi-Level Representation Learning Fusion-Based Maximum Entropy Subspace Clustering for Hyperspectral Band Selection

Remote Sensing
As one of the most important techniques for hyperspectral image dimensionality reduction, band selection has received considerable attention, whereas self-representation subspace clustering-based band selection algorithms have received quite a lot of ...
Yulei Wang, Haipeng Ma, Yuchao Yang, Enyu Zhao, Meiping Song, Chunyan Yu   +5 more
doaj   +1 more source

Unsupervised Hyperspectral Band Selection using Clustering and Single-Layer Neural Network

Revue Française de Photogrammétrie et de Télédétection, 2018
Hyperspectral images provide rich  spectral details of the observed scene by exploiting contiguous bands. But, the processing of such images becomes heavy, due to the high dimensionality.
Mateus Habermann, Vincent Frémont, Elcio Hideiti Shiguemori   +2 more
doaj   +1 more source

Generative AI, ESG Sensemaking, and Environmental Performance: an OIPT Perspective

Business Strategy and the Environment, EarlyView.
ABSTRACT Despite growing enthusiasm for generative artificial intelligence (GenAI) in sustainability management, it remains unclear how such technologies translate vast ESG information into meaningful environmental outcomes. This study addresses this gap by investigating how ESG sensemaking capability mediates the relationship between GenAI integration
Surajit Bag, Gautam Srivastava, Susmi Routray, Andrea Chiarini   +3 more
wiley   +1 more source

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

Ensemble Identification of Spectral Bands Related to Soil Organic Carbon Levels over an Agricultural Field in Southern Ontario, Canada

Remote Sensing, 2019
The recent use of hyperspectral remote sensing imagery has introduced new opportunities for soil organic carbon (SOC) assessment and monitoring.
Ahmed Laamrani, Aaron A. Berg, Paul Voroney, Hannes Feilhauer, Line Blackburn, Michael March, Phuong D. Dao, Yuhong He, Ralph C. Martin   +8 more
doaj   +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

BCARS Simulated Phantom Dataset for Evaluation of Processing Pipelines

Journal of Raman Spectroscopy, EarlyView.
A tissue phantom, containing fingerprint Raman spectra at each pixel, is developed to evaluate Raman signal processing pipelines. The phantom is created from a BCARS image of a murine hepatic tissue. ABSTRACT Broadband coherent anti‐Stokes Raman scattering (BCARS) microscopy is a powerful label‐free biological imaging technique, but the raw signal ...
Jessica Z. Dixon, Eric G. Baker, Charles H. Camp, Sidharth Laxminarayan, Abigail Bonde, Marcus T. Cicerone   +5 more
wiley   +1 more source

The contribution of vibrational spectroscopy and data analytics towards the achievement of the global sustainability goals

Journal of the Science of Food and Agriculture, EarlyView.
Abstract The United Nations Sustainable Development Goals (UN SDGs) were defined to improve the quality of life of the global population particularly regarding social and economic aspects, with a major focus on environmental sustainability. The incorporation of digital technologies into the agri‐food sector has become a key enabler in increasing the ...
Daniel Cozzolino, Louwrens C Hoffman
wiley   +1 more source