Results 71 to 80 of about 12,889,375 (285)
Fuzzy spectral and spatial feature integration for classification of nonferrous materials in hyperspectral data [PDF]
, 2009 Hyperspectral data allows the construction of more elaborate models to sample the properties of the nonferrous materials than the standard RGB color representation.
Iriondo, Pedro M. +4 more
core +2 more sources
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
Capsule Networks for Hyperspectral Image Classification [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2019 Convolutional neural networks (CNNs) have recently exhibited an excellent performance in hyperspectral image classification tasks. However, the straightforward CNN-based network architecture still finds obstacles when effectively exploiting the relationships between hyperspectral imaging (HSI) features in the spectral–spatial domain, which is a key ...
Mercedes Eugenia Paoletti +6 more
openaire +2 more sources
Advanced Intelligent Discovery, EarlyView.Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley +1 more source
Advanced Intelligent Systems, EarlyView.As food insecurity and global food demands surge, artificial intelligence (AI)‐based technologies offer promising opportunities to reduce food loss and waste. In this perspective, current AI adoption across the food supply chain is assessed using various academic, industry, and policy sources.
Akansha Prasad +5 more
wiley +1 more source
Remote SensingHyperspectral remote sensing provides rich spectral information and has been widely used in fine-grained land-cover classification and forest monitoring.
Xinying Liu +6 more
doaj +1 more source
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
Applications in Plant Sciences, EarlyView.Abstract Premise Road verges function as refuges for semi‐natural species, but they can also facilitate the spread of non‐native plants such as Lupinus polyphyllus. Unmanned aerial vehicle (UAV)–based remote sensing is a promising tool for mapping these species; however, its application in roadside contexts remains limited.
Elin L. Blomqvist +3 more
wiley +1 more source
European Journal of Remote Sensing, 2020 In recent years, deep learning has drawn increasing attention in the field of hyperspectral remote sensing image classification and has achieved great success.
Xibing Zuo +5 more
doaj +1 more source