Results 81 to 90 of about 15,264 (300)
Remote Sensing, 2019 This paper assesses the performance of DoTRules—a dictionary of trusted rules—as a supervised rule-based ensemble framework based on the mean-shift segmentation for hyperspectral image classification.
Majid Shadman Roodposhti +3 more
doaj +1 more source
Classification for hyperspectral imaging [PDF]
, 2014 Hyperspectral Imaging is a method of collecting and processing the information across pre-defined electromagnetic spectrum. These measurements make it possible to derive a continuous spectrum for each pixel of the image. After necessary adjustments these image spectra can be compared with database of reflectance spectra in order to recognise tested ...
Polak, Adam +3 more
openaire +1 more source
Vector Attribute Profiles for Hyperspectral Image Classification [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2016 Morphological attribute profiles are among the most prominent spectral–spatial pixel description methods. They are efficient, effective, and highly customizable multiscale tools based on hierarchical representations of a scalar input image. Their application to multivariate images in general and hyperspectral images in particular has been so far ...
Erchan Aptoula +2 more
openaire +4 more sources
Guiding and Manipulating Light Fields in Microstructured Liquid Crystals
Advanced Physics Research, EarlyView.This review summarizes recent advances in guided‐wave optics enabled by microstructured liquid crystal (LC) devices, covering their fundamental material properties, key degree of freedom for dynamic light field manipulations. The advances of linear guided‐wave optics, nonlinear‐optics with spatial optical solitons, and microlasers in LC‐based devices ...
Shan‐shan Chang +2 more
wiley +1 more source
Illumination invariance and shadow compensation on hyperspectral images [PDF]
, 2014 To obtain intrinsic reflectance of the scene by hyperspectral imaging systems has been a scientific and engineering challenge. Factors such as illumination variations, atmospheric effects and viewing geometries are common artefacts which modulate the way
Ibrahim, Izzati
core
, 2013 With increasing applications of hyperspectral imagery (HSI) in agriculture, mineralogy, military, and other fields, one of the fundamental tasks is accurate detection of the target of interest.
Li, Xiaohui +3 more
core +1 more source
, 2022 Recently, convolutional neural networks (CNNs) have demonstrated impressive capabilities in the representation and classification of hyperspectral remote sensing images. Traditional CNNs require massive data to sufficiently train the network.
Lijuan Duan +11 more
core +1 more source
Tackling cancer stemness with nanotechnology in the era of precision medicine
BMEMat, EarlyView.Precise customization of nanoparticles (NPs) enables active targeting of cancer stem cells (CSCs), thereby improving drug delivery and therapeutic efficacy. NP‐based probing enhances CSC detection through imaging and liquid biopsy, whereas diverse therapeutic payloads improve therapeutic outcomes.
Shaolei Guo +9 more
wiley +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
SSATNet: Spectral-spatial attention transformer for hyperspectral corn image classification
Frontiers in Plant ScienceHyperspectral images are rich in spectral and spatial information, providing a detailed and comprehensive description of objects, which makes hyperspectral image analysis technology essential in intelligent agriculture.
Bin Wang +7 more
doaj +1 more source