Results 51 to 60 of about 57,062 (333)
A scalable dataflow accelerator for real time onboard hyperspectral image classification
, 2016 © Springer International Publishing Switzerland 2016.Real-time hyperspectral image classification is a necessary primitive in many remotely sensed image analysis applications.
C Gustavo +8 more
core +1 more source
Advanced Functional Materials, EarlyView.This study presents a dynamic interaction between liquid resins and photopolymerized structures enabled by an in situ light‐writing setup. By controlling a three‐phase interface through localized photopolymerization, which provides physical confinement for the remaining uncured resin regions, the approach establishes a programmable pathway that ...
Kibeom Kim +3 more
wiley +1 more source
ISPRS International Journal of Geo-Information, 2021 Generation of a thematic map is important for scientists and agriculture engineers in analyzing different crops in a given field. Remote sensing data are well-accepted for image classification on a vast area of crop investigation.
Shiuan Wan, Mei-Ling Yeh, Hong-Lin Ma
doaj +1 more source
Programmable Spectrometry -- Per-pixel Classification of Materials using Learned Spectral Filters
, 2019 Many materials have distinct spectral profiles. This facilitates estimation of the material composition of a scene at each pixel by first acquiring its hyperspectral image, and subsequently filtering it using a bank of spectral profiles.
Sankaranarayanan, Aswin C. +1 more
core +1 more source
Advanced Materials, EarlyView.AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Applied SciencesIn the field of hyperspectral image classification, deep learning technology, especially convolutional neural networks, has achieved remarkable progress.
Laiying Fu +3 more
doaj +1 more source
A Sparse Representation-Based Sample Pseudo-Labeling Method for Hyperspectral Image Classification
Remote Sensing, 2020 Hyperspectral image classification methods may not achieve good performance when a limited number of training samples are provided. However, labeling sufficient samples of hyperspectral images to achieve adequate training is quite expensive and difficult.
Binge Cui +4 more
doaj +1 more source
Masked Graph Convolutional Network for Small Sample Classification of Hyperspectral Images
Remote Sensing, 2023 The deep learning method has achieved great success in hyperspectral image classification, but the lack of labeled training samples still restricts the development and application of deep learning methods.
Wenkai Liu +5 more
doaj +1 more source
A new bandwidth selection criterion for using SVDD to analyze hyperspectral data
, 2019 This paper presents a method for hyperspectral image classification that uses support vector data description (SVDD) with the Gaussian kernel function. SVDD has been a popular machine learning technique for single-class classification, but selecting the ...
Baumgardner +6 more
core +1 more source
Advanced Materials, EarlyView.Merging materials processing tricks inspired by mussel and mistletoe fiber fabrication, solutions of cationic mussel byssus proteins were mixed with modified anionic nanocrystalline cellulose, producing distinctive core‐shell condensates. Simple processing of condensate suspensions using freeze‐drying produced hierarchically structured porous protein ...
Hamideh R. Alanagh +9 more
wiley +1 more source