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Angel James Medina Medina, Rolando Salas López, Jhon Antony Zabaleta Santisteban, Katerin Meliza Tuesta Trauco, Efrain Yury Turpo Cayo, Nixon Huaman Haro, Manuel Oliva Cruz and Darwin Gómez Fernández
One of the world?s major agricultural crops is rice (Oryza sativa), a staple food for more than half of the global population. In this research, synthetic aperture radar (SAR) and optical images are used to analyze the monthly dynamics of this crop in th...
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Tao Tang, Yuting Cui, Rui Feng and Deliang Xiang
With the development of deep learning in the field of computer vision, convolutional neural network models and attention mechanisms have been widely applied in SAR image target recognition. The improvement of convolutional neural network attention in exi...
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Junyi Chen, Yanyun Shen, Yinyu Liang, Zhipan Wang and Qingling Zhang
Aircraft detection in SAR images of airports remains crucial for continuous ground observation and aviation transportation scheduling in all weather conditions, but low resolution and complex scenes pose unique challenges. Existing methods struggle with ...
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Sara Zollini, Donatella Dominici, Maria Alicandro, María Cuevas-González, Eduard Angelats, Francesca Ribas and Gonzalo Simarro
Coastal environments are dynamic ecosystems, constantly subject to erosion/accretion processes. Erosional trends have unfortunately been intensifying for decades due to anthropic factors and an accelerated sea level rise might exacerbate the problem. It ...
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Hui Zhou, Peng Chen, Yingqiu Li and Bo Wang
Ship detection in large-scene offshore synthetic aperture radar (SAR) images is crucial in civil and military fields, such as maritime management and wartime reconnaissance. However, the problems of low detection rates, high false alarm rates, and high m...
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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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Siyi Li, Guowang Jin and Jiahao Li
Flooding is one of the most frequently occurring meteorological disasters nowadays, and its occurrence can cause significant socio-economic losses. Aiming at the problem that traditional optical remote sensing makes it difficult to monitor floods, this p...
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Sivapriya Sethu Ramasubiramanian, Suresh Sivasubramaniyan and Mohamed Fathimal Peer Mohamed
Detection and classification of icebergs and ships in synthetic aperture radar (SAR) images play a vital role in marine surveillance systems even though available adaptive threshold methods give satisfying results on detection and classification for ship...
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Xiaoqin Lian, Xue Huang, Chao Gao, Guochun Ma, Yelan Wu, Yonggang Gong, Wenyang Guan and Jin Li
In recent years, the advancement of deep learning technology has led to excellent performance in synthetic aperture radar (SAR) automatic target recognition (ATR) technology. However, due to the interference of speckle noise, the task of classifying SAR ...
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Ambroise Guiot, Fatima Karbou, Guillaume James and Philippe Durand
Monitoring variations in the extent of wet snow over space and time is essential for many applications, such as hydrology, mountain ecosystems, meteorology and avalanche forecasting. The Synthetic Aperture Radar (SAR) measurements from the Sentinel-1 sat...
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