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Published in 2020 at "Pest Management Science"
DOI: 10.1002/ps.5758
Abstract: Abstract BACKGROUND Detection and diagnosis of emerging arthropod outbreaks in horticultural glasshouse crops, such as bok choy and spinach, is both important and challenging. A major challenge is to accurately detect and diagnose arthropod outbreaks…
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Keywords:
choy spinach;
bok choy;
hyperspectral remote;
remote sensing ... See more keywords
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Published in 2017 at "Neural Computing and Applications"
DOI: 10.1007/s00521-017-3279-y
Abstract: Semi-supervised feature extraction methods are an important focus of interest in data mining and machine learning areas. These methods are improved methods based on learning from a combination of labeled and unlabeled data. In this…
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Keywords:
semi supervised;
method;
remote sensing;
feature extraction ... See more keywords
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Published in 2019 at "Precision Agriculture"
DOI: 10.1007/s11119-019-09640-2
Abstract: In karst landscapes stony soils have little water holding capacity; the rational use of water for irrigation therefore plays an important management role. Because the water holding capacity is not homogenous, precision agriculture approaches would…
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Keywords:
drought stress;
water;
hyperspectral remote;
grapevine drought ... See more keywords
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Published in 2018 at "Environmental Science and Pollution Research"
DOI: 10.1007/s11356-018-3745-9
Abstract: Cadmium (Cd) contaminated rice has become a global food security issue. Hyperspectral remote sensing can do rapid and nondestructive monitoring of environmental stress in plant. To realize the nondestructive detection of Cd in brown rice…
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Keywords:
rice;
rice harvest;
remote sensing;
brown rice ... See more keywords
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Published in 2017 at "Isprs Journal of Photogrammetry and Remote Sensing"
DOI: 10.1016/j.isprsjprs.2017.03.009
Abstract: Remote detection and mapping of hydrocarbons (PHCs) in situ in continental areas is still an operational challenge due to the small scale of the occurrences and the mix of spectral signatures of PHCs and mineral…
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Keywords:
detection;
mineral substrates;
exploration;
remote sensing ... See more keywords
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Published in 2020 at "Isprs Journal of Photogrammetry and Remote Sensing"
DOI: 10.1016/j.isprsjprs.2020.06.023
Abstract: Abstract Bananas and plantains provide food and income for more than 50 million smallholder farmers in East and Central African (ECA) countries. However, banana productivity generally achieves less than optimal yield potential (
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Keywords:
potential situ;
remote sensing;
situ hyperspectral;
differentiating banana ... See more keywords
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Published in 2018 at "Ore Geology Reviews"
DOI: 10.1016/j.oregeorev.2017.11.023
Abstract: Abstract Economic mineral deposits are commonly associated with zones of intense hydrothermal alteration. Space borne hyperspectral remote sensing is one of the recent techniques that enable the identification of hydrothermally altered and weathered minerals. In…
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Keywords:
base;
kumaon himalaya;
base metal;
hyperspectral remote ... See more keywords
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Published in 2019 at "Remote Sensing Applications: Society and Environment"
DOI: 10.1016/j.rsase.2019.100270
Abstract: Abstract Imaging spectroscopy is a proven technology for identifying and mapping the constituents of soils based on their spectral signatures, the variation of their reflectance or emissivity across different wavelengths, in the visible and infrared…
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Keywords:
hyperspectral remote;
alternative correlate;
soil;
detection alternative ... See more keywords
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Published in 2019 at "Spectroscopy Letters"
DOI: 10.1080/00387010.2019.1649701
Abstract: Abstract Flowering phenology, as a sensitive bio-indicator to climate change, has been attracting increasing concern. However, less information is available so far for quantifying flowering phenological stages by use of hyperspectral remote sensing in winter…
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Keywords:
winter wheat;
remote sensing;
flowering phenology;
phenology ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2932909
Abstract: In land-use classification of hyperspectral remote sensing (RS) images, traditional classification methods often experience large amount of datasets and low efficiency. To solve these problems, a fast machine-learning method, the extreme learning machine (ELM) algorithm,…
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Keywords:
optimization;
hyperspectral remote;
optimization methods;
classification accuracy ... See more keywords
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Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3195639
Abstract: Graph neural network has an excellent performance in obtaining the similarity relationship of samples, so it has been widely used in computer vision. But the hyperspectral remote sensing image (HSI) has some problems, such as…
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Keywords:
based semisupervised;
remote sensing;
hyperspectral remote;
classification ... See more keywords