Results 71 to 80 of about 16,742 (260)
Fast Spectral Clustering for Unsupervised Hyperspectral Image Classification
Hyperspectral image classification is a challenging and significant domain in the field of remote sensing with numerous applications in agriculture, environmental science, mineralogy, and surveillance.
Yang Zhao, Yuan Yuan, Qi Wang
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A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi +5 more
wiley +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
Metalens‐Enabled Twisted Chromatic Dispersion
We successfully demonstrate visible broadband twisted dispersion metalenses. As a proof of concept, we realized two distinct devices: the conical helical and the spring‐like dispersion‐controlled metalenses. These results rigorously validate the universality of our approach in customizing arbitrary continuous 3D dispersion trajectories, thereby ...
Shiyu Zheng +3 more
wiley +1 more source
ABSTRACT Satellite remote sensing is among the most significant modern methodologies supporting field archaeology. In addition to its efficiency in identifying archaeological sites, remote sensing offers a safe and cost‐effective approach in conflict zones.
Amal Al Kassem +5 more
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Deep learning-based approaches to hyperspectral image analysis have attracted large attention and exhibited high performance in image classification tasks. However, deployment of deep learning-based hyperspectral image analysis systems is challenging due
Eungjoo Lee +3 more
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Cutting Through the Green: A Case for Grassland Archaeology Using UAV Multispectral Data
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
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Generative AI, ESG Sensemaking, and Environmental Performance: an OIPT Perspective
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
Hyperspectral images (HSIs) contain abundant spectral and spatial structural information, but they are inevitably contaminated by a variety of noises during data reception and transmission, leading to image quality degradation and subsequent application ...
Chun He, Youhua Wei, Ke Guo, Hongwei Han
doaj +1 more source

