Deep-Learning-Driven High-Fidelity In Vivo Hyperspectral Fluorescence Imaging Under Extreme Photon-Limited Conditions. [PDF]
Adv Sci (Weinh)Highly overlapping fluorescent signals become distinguishable in photon‐limited living organisms via advanced imaging with intelligent reconstruction. The resulting in vivo hyperspectral imaging capability reveals nanoplastic uptake and circulation in live zebrafish, providing a new approach for studying complex biological and environmental processes ...
Li R +11 more
europepmc +2 more sources
HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image [PDF]
CoRR, 2018 With the development of deep learning, the performance of hyperspectral image (HSI) classification has been greatly improved in recent years. The shortage of training samples has become a bottleneck for further improvement of performance. In this paper, we propose a novel convolutional neural network framework for the characteristics of hyperspectral ...
Xiaosong Zhao
exaly +4 more sources
HSI-MSER: Hyperspectral Image Registration Algorithm Based on MSER and SIFT [PDF]
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 This work was supported in part by Ministerio de Ciencia e Innovación, Government of Spain [grant number PID2019-104834GB-I00], and Consellería de Cultura, Educación e Universidade [grant numbers ED431C 2018/19, and accreditation 2019-2022 ED431G-2019/04]. All are co--funded by the European Regional Development Fund (ERDF).
Francisco Arguello +2 more
exaly +6 more sources
Non-Destructive Analysis of Phenolic and Flavonoid Contents in Medicinal Plant Powders Using Hyperspectral Imaging and Variable Selection. [PDF]
Anal Sci AdvABSTRACT Phenolic and flavonoid contents in medicinal plants are essential to their growth and development and provide numerous health benefits, yet their quantification using traditional wet chemistry is labor‐intensive and time‐consuming. This study utilized the combination of two benchtop hyperspectral imaging (HSI) systems, namely short‐wave ...
Joshi R +9 more
europepmc +2 more sources
Detection of Frost-Damaged Maize Kernels for Food Quality Screening Using Hyperspectral Imaging and 2D-COS-Assisted Deep Learning. [PDF]
Food Sci NutrThis work presents a nondestructive strategy for identifying frost‐damaged maize kernels using hyperspectral imaging (900–1700 nm) combined with 2D‐COS‐assisted deep learning. MSC preprocessing was adopted, and 432 frost‐damage‐related characteristic bands were extracted by 2D‐COS.
Nan J +7 more
europepmc +2 more sources
An Adaptive Support Vector Machine Optimized by an Improved Starfish Optimization Algorithm for Hyperspectral Image Classification [PDF]
BiomimeticsThis study proposes an adaptive Support Vector Machine (SVM) classification method based on an enhanced Starfish Optimization Algorithm (SFOAE-SVM) for hyperspectral image (HSI) classification.
Yi Zhang, Changyi Feng, Yong Xu
doaj +2 more sources
Improved Transformer Net for Hyperspectral Image Classification
Remote Sensing, 2021 In recent years, deep learning has been successfully applied to hyperspectral image classification (HSI) problems, with several convolutional neural network (CNN) based models achieving an appealing classification performance.
Yuhao Qing +3 more
doaj +3 more sources
SOFT COMPUTING APPROACHES FOR HYPERSPECTRAL IMAGE CLASSIFICATION [PDF]
ICTACT Journal on Soft Computing, 2020 Hyperspectral image classification is one of the most emerging form of image classification. It is able to convey information about an image in a more detailed way as compared to RGB or multispectral data.
H S Prasantha +3 more
doaj +1 more source
Remote Sensing, 2022 Hyperspectral sharpening has been considered an important topic in many earth observation applications. Many studies have been performed to solve the Visible-Near-Infrared (Vis-NIR) hyperpectral sharpening problem, but there is little research related to
Sihan Huang, David Messinger
doaj +1 more source
Hyperspectral Super-Resolution Via Joint Regularization of Low-Rank Tensor Decomposition
Remote Sensing, 2021 The hyperspectral image super-resolution (HSI-SR) problem aims at reconstructing the high resolution spatial–spectral information of the scene by fusing low-resolution hyperspectral images (LR-HSI) and the corresponding high-resolution multispectral ...
Meng Cao, Wenxing Bao, Kewen Qu
doaj +1 more source