[HTML][HTML] Current advances in imaging spectroscopy and its state-of-the-art applications
Imaging spectroscopy integrates traditional computer vision and spectroscopy into a single
system and has gained widespread acceptance as a non-destructive scientific instrument for …
system and has gained widespread acceptance as a non-destructive scientific instrument for …
[HTML][HTML] Does environmental data increase the accuracy of land use and land cover classification?
LB Zeferino, LFT de Souza, CH do Amaral… - International Journal of …, 2020 - Elsevier
Optical image classification converts spectral data into thematic information from the spectral
signature of each object in the image. However, spectral separability is influenced by …
signature of each object in the image. However, spectral separability is influenced by …
[HTML][HTML] Hyperspectral image classification based on non-parallel support vector machine
G Liu, L Wang, D Liu, L Fei, J Yang - Remote Sensing, 2022 - mdpi.com
Support vector machine (SVM) has a good effect in the supervised classification of
hyperspectral images. In view of the shortcomings of the existing parallel structure SVM, this …
hyperspectral images. In view of the shortcomings of the existing parallel structure SVM, this …
[HTML][HTML] Optimal segmentation scale parameter, feature subset and classification algorithm for geographic object-based crop recognition using multisource satellite …
L Yang, LR Mansaray, J Huang, L Wang - Remote Sensing, 2019 - mdpi.com
Geographic object-based image analysis (GEOBIA) has been widely used in the remote
sensing of agricultural crops. However, issues related to image segmentation, data …
sensing of agricultural crops. However, issues related to image segmentation, data …
Optimal multi-temporal Sentinel-1A SAR imagery for paddy rice field discrimination; a recommendation for operational mapping initiatives
LR Mansaray, VTS Kabba, L Zhang… - … Applications: Society and …, 2021 - Elsevier
Phenology-based rice mapping has mostly employed all satellite data over the growing
season. This approach is not only time consuming but also requires huge data storage and …
season. This approach is not only time consuming but also requires huge data storage and …
[HTML][HTML] Hyperspectral image classification based on a least square bias constraint additional empirical risk minimization nonparallel support vector machine
G Liu, L Wang, D Liu - Remote Sensing, 2022 - mdpi.com
Hyperspectral image classification technology is important for the application of
hyperspectral technology. Support vector machines (SVMs) work well in supervised …
hyperspectral technology. Support vector machines (SVMs) work well in supervised …
[PDF][PDF] Int J Appl Earth Obs Geoinformation
LB Zeferino, LFT de Souza, CH do Amaral… - researchgate.net
Optical image classification converts spectral data into thematic information from the spectral
signature of each object in the image. However, spectral separability is influenced by …
signature of each object in the image. However, spectral separability is influenced by …
[PDF][PDF] SPECTRAL DISCRIMINATION AND INDEX DEVELOPMENT OF ROOFING MATERIALS AND CONDITIONS USING FIELD SPECTROSCOPY AND …
SHB SAMSUDIN - 2016 - psasir.upm.edu.my
The development of remote sensing technology has improved urban mapping tasks to
provide essential information in urban monitoring and urban management. The motivation …
provide essential information in urban monitoring and urban management. The motivation …
[引用][C] Multitemporal co-polar x-band sar data classification as a tool for paddy-rice phenology estimation
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