Results 101 to 110 of about 11,136 (312)
Remote Sensing, 2018 When confronted with limited labelled samples, most studies adopt an unsupervised feature learning scheme and incorporate the extracted features into a traditional classifier (e.g., support vector machine, SVM) to deal with hyperspectral imagery ...
Cong Wang +3 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed +15 more
wiley +1 more source
Spatial Cell Death and Oxidative Stress Dynamics in Gas Plasma‐Treated Tumor Tissues
Advanced NanoBiomed Research, EarlyView.Schematic representation of the four experimental models to study tissue penetration and oxidation. Four tissue models were used. Human pancreatic cancer cells were grown on the chorioallantois membrane of chicken embryos and gas plasma‐treated in ovo, murine colorectal tumor tissue was gas plasma‐exposed ex vivo, murine squamous cell carcinoma cells ...
Anke Schmidt +4 more
wiley +1 more source
Hyperspectral Image Resolution Enhancement Based on Spectral Unmixing and Information Fusion
, 2011 Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels.
Avbelj, Janja +4 more
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Spatial analysis for colon biopsy classification from hyperspectral imagery [PDF]
, 2008 Automatic classification of histology images, the objective of our research, is aimed at supporting the pathologists in their diagnosis. In this paper, we present a comparative study between 3D spectral/spatial analysis (SSA) and 2D spatial analysis (SA ...
Rajpoot, Nasir M. (Nasir Mahmood) +1 more
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Remote Sensing, 2019 The precise classification of crop types is an important basis of agricultural monitoring and crop protection. With the rapid development of unmanned aerial vehicle (UAV) technology, UAV-borne hyperspectral remote sensing imagery with high spatial ...
Lifei Wei +6 more
doaj +1 more source
Unmixing and anomaly detection in hyperspectral data due to cluster variation and local information
, 2022 Paper 76952GThis paper presents a novel method for anomaly detection based on a cluster unmixing approach. Several algorithms for endmember extraction and unmixing have been reported in literature.
Huber, J., Middelmann, W., Maerker, J.
core +1 more source
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
Explorable 3D Hyperspectral Models from Multi-Angle Gimballed LWIR Pushbroom Imagery
Remote SensingHyperspectral imaging in the long-wave infrared (LWIR) range enables identification of chemical compositions and material properties, but reconstructing 3D models from gimballed pushbroom sensors remains challenging because their unique acquisition ...
Nikolay Golosov +2 more
doaj +1 more source
, 2011 The classification of hyperspectral images on heterogeneous environments without prior knowledge about the study area is a challenging task. Finding potential pure spectral signatures or endmembers (EM) of the various surface materials within an image is
Mende, Andre +4 more
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