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Current State of Hyperspectral Remote Sensing for Early Plant Disease Detection: A Review [PDF]
Sensors, 2022 The development of hyperspectral remote sensing equipment, in recent years, has provided plant protection professionals with a new mechanism for assessing the phytosanitary state of crops.
Anton Terentev +3 more
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Research and application of UAV-based hyperspectral remote sensing for smart city construction
Cognitive Robotics, 2022 Hyperspectral remote sensing has been an important technical means to obtain more refined information and provide rich, accurate, and reasonable data for the quantitative analysis and delicacy management of a ''smart city''.
Boxiong Yang +6 more
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Research on Classification of Grassland Degeneration Indicator Objects Based on UAV Hyperspectral Remote Sensing and 3D_RNet-O Model [PDF]
SensorsReal-time and high-precision land cover classification is the foundation for efficient and quantitative research on grassland degradation using remote sensing techniques.
Eerdoumutu Jin +4 more
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Unsupervised Domain Adaptation With Dense-Based Compaction for Hyperspectral Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Enormously hard work of label obtaining leads to the lack of enough annotated samples in the hyperspectral imagery (HSI). The mentioned reality inferred the unsupervised classification performance barely satisfactorily.
Chunyan Yu +4 more
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A Spatial-Enhanced LSE-SFIM Algorithm for Hyperspectral and Multispectral Images Fusion
Remote Sensing, 2021 The fusion of a hyperspectral image (HSI) and multispectral image (MSI) can significantly improve the ability of ground target recognition and identification.
Yulei Wang +4 more
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Orthogonal Subspace Projection Target Detector for Hyperspectral Anomaly Detection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Orthogonal subspace projection (OSP) is a versatile hyperspectral imaging technique which has shown great potential in dimensionality reduction, target detection, spectral unmixing, etc. However, due to its inherent requirement of prior target knowledge,
Chein-I Chang, Hongju Cao, Meiping Song
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SGD-SM 2.0: an improved seamless global daily soil moisture long-term dataset from 2002 to 2022 [PDF]
Earth System Science Data, 2022 The drawbacks of low-coverage rate in global land inevitably exist in satellite-based daily soil moisture products because of the satellite orbit covering scopes and the limitations of soil moisture retrieving models.
Q. Zhang +4 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Target extraction can provide a prior knowledge for spectral unmixing, unsupervised hyperspectral image classification, and unsupervised target detection tasks, which is of great practice.
Xiaodi Shang +4 more
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IET Image Processing, 2022 Although hyperspectral data, especially spaceborne images, are rich in spectral information, their spatial resolution is usually low due to the limitation of sensor design and other factors.
Haoyang Yu +5 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Convolutional neural networks (CNN) have led to a successful breakthrough for hyperspectral image classification (HSIC). Due to the intrinsic spatial-spectral specificities of a hyperspectral cube, feature extraction with 3-D convolution operation is a ...
Chunyan Yu +4 more
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