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Jakub Langhammer, Theodora Lendzioch and Jakub ?olc
The detection and mapping of riverscapes with Unmanned Aerial Vehicles (UAVs, drones) provide detailed, reliable, and operable spatial information in hydrological sciences, enhancing conventional field survey techniques. In this study, we present the res...
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Li He, Shasha Ji, Kunlun Xin, Zewei Chen, Lei Chen, Jun Nan and Chenxi Song
Hydraulic monitoring data is critical for optimizing drainage system design and predicting system performance, particularly in the establishment of data-driven hydraulic models. However, anomalies in monitoring data, caused by sensor failures and network...
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Jie Wu, Yongjin He, Chengyu Xu, Xiaoping Jia, Yule Huang, Qianru Chen, Chuyue Huang, Armin Dadras Eslamlou and Shiping Huang
Crack detection is an important task in bridge health monitoring, and related detection methods have gradually shifted from traditional manual methods to intelligent approaches with convolutional neural networks (CNNs) in recent years. Due to the opaque ...
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Thomas Di Martino, Bertrand Le Saux, Régis Guinvarc?h, Laetitia Thirion-Lefevre and Elise Colin
With an increase in the amount of natural disasters, the combined use of cloud-penetrating Synthetic Aperture Radar and deep learning becomes unavoidable for their monitoring. This article proposes a methodology for forest fire detection using unsupervis...
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Filippos Pelekoudas-Oikonomou, José C. Ribeiro, Georgios Mantas, Georgia Sakellari and Jonathan Gonzalez
The Internet of Medical Things (IoMT) has risen significantly in recent years and has provided better quality of life by enabling IoMT-based health monitoring systems. Despite that fact, innovative security mechanisms are required to meet the security co...
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