|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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 ...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Samantha Schultz, Koreen Millard, Samantha Darling and René Chénier
Peatlands provide vital ecosystem and carbon services, and Canada is home to a significant peatland carbon stock. Global climate warming trends are expected to lead to increased carbon release from peatlands, as a consequence of drought and wildfire. Mon...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wenzhao Li, Dongfeng Li and Zheng N. Fang
Numerous algorithms have been developed to automate the process of delineating water surface maps for flood monitoring and mitigation purposes by using multiple sources such as satellite sensors and digital elevation model (DEM) data. To better understan...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ogbaje Andrew, Armando Apan, Dev Raj Paudyal and Kithsiri Perera
The accuracy of most SAR-based flood classification and segmentation derived from semi-automated algorithms is often limited due to complicated radar backscatter. However, deep learning techniques, now widely applied in image classifications, have demons...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wenhai Cheng, Qunying Zhang, Jiaming Dong, Haiying Wang and Xiaojun Liu
Resolution and mapping bandwidth are the two most important image performance indicators that reflect satellite synthetic aperture radar (SAR) imaging reconnaissance capability. The PRI-staggered signal can simultaneously achieve high resolution in azimu...
ver más
|
|
|
|
|
|
|
|
|
|
|
Manuel Nhangumbe, Andrea Nascetti and Yifang Ban
Floods are one of the most frequent natural disasters worldwide. Although the vulnerability varies from region to region, all countries are susceptible to flooding. Mozambique was hit by several cyclones in the last few decades, and in 2019, after cyclon...
ver más
|
|
|
|
|
|