Results 111 to 120 of about 35,627 (298)
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
Hyperspectral imagery super-resolution by sparse representation and spectral regularization
EURASIP Journal on Advances in Signal Processing, 2011 For the instrument limitation and imperfect imaging optics, it is difficult to acquire high spatial resolution hyperspectral imagery. Low spatial resolution will result in a lot of mixed pixels and greatly degrade the detection and recognition ...
Zhao Yongqiang +5 more
doaj
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 +3 more
wiley +1 more source
Weighted Sparseness-Based Anomaly Detection for Hyperspectral Imagery. [PDF]
Sensors (Basel), 2023 Lian X +6 more
europepmc +1 more source
Hyperspectral imagery super-resolution
, 2020 Hyperspectral (HS) imagery consists of hundred of narrow contiguous bands extending beyond the visible spectrum. It is a three dimensional data cube with two dimensional spatial information and a spectral dimension. Despite having high spectral resolution, HS images have lower spatial resolution due to technological restrictions.
openaire +1 more source
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 +7 more
wiley +1 more source
Quantification of Photosynthetic Pigments in Neopyropia yezoensis Using Hyperspectral Imagery. [PDF]
Plant Phenomics, 2023 Che S +5 more
europepmc +1 more source
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
Postprocessing for Fine Classification of Crops in UAV Hyperspectral Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingUnmanned aerial vehicle (UAV) hyperspectral imagery has become a vital tool for crop monitoring, delivering rich spatial information and detailed spectral properties of crops.
Qikai Lu +4 more
doaj +1 more source
Retrieval of carbon content and biomass from hyperspectral imagery over cultivated areas. [PDF]
ISPRS J Photogramm Remote Sens, 2022 Wocher M, Berger K, Verrelst J, Hank T.
europepmc +1 more source