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Muhammad Yasir, Abdoul Jelil Niang, Md Sakaouth Hossain, Qamar Ul Islam, Qian Yang and Yuhang Yin
We aimed to improve the performance of ship detection methods in synthetic aperture radar (SAR) images by utilizing machine learning (ML) and artificial intelligence (AI) techniques. The maritime industry faces challenges in collecting precise data due t...
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Haya M. Alogayell, Eman Mohamed M. EL-Bana and Mohamed Abdelfattah
The present work focuses on a comprehensive hydrochemical assessment of groundwater within a shallow aquifer located in the central region of Saudi Arabia. This aquifer serves as the principal source of groundwater supply for agricultural irrigation purp...
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Fang Ding, Lin Wang, Iryna Dronova and Kun Cao
Beijing-1 and ENVISAT ASAR images were used to classify wetland aquatic macrophytes in terms of their plant functional types (PFTs) over the Poyang Lake region, China. Speckle noise filtering, systematic sensor calibration within the same polarization or...
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Candela Maceiras, José M. Pérez-Canosa, Diego Vergara and José A. Orosa
The present paper shows an original study of more than 163 ship accidents in Spain showing which of the usually employed variables are related to each type of vessel accident due to the lack of information in this region. To this end, research was carrie...
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Rui Zhang, Xinming Tang, Shucheng You, Kaifeng Duan, Haiyan Xiang and Hongxia Luo
Remote sensing data plays an important role in classifying land use/land cover (LULC) information from various sensors having different spectral, spatial and temporal resolutions. The fusion of an optical image and a synthetic aperture radar (SAR) image ...
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