Real-time object detection based on uav remote sensing: A systematic literature review

Z Cao, L Kooistra, W Wang, L Guo, J Valente - Drones, 2023 - mdpi.com
Real-time object detection based on UAV remote sensing is widely required in different
scenarios. In the past 20 years, with the development of unmanned aerial vehicles (UAV) …

ROI-constrained visualization of flood scenes to improve perception efficiency

J You, J Zhu, W Li, Y Guo, L Fu… - International Journal of …, 2023 - Taylor & Francis
Efficient and intuitive representation of floods can improve people's perception, which is
useful for flood emergency management and decision making. However, the current …

[HTML][HTML] An integrated convolutional neural network and sorting algorithm for image classification for efficient flood disaster management

MA Islam, SI Rashid, NUI Hossain, R Fleming… - Decision Analytics …, 2023 - Elsevier
Drones are used for post-flood disaster management and delivering relief goods to flood-
affected areas. Autonomous drones are an alternative means of prioritizing assistance due …

Comparative study of real-time semantic segmentation networks in aerial images during flooding events

F Safavi, M Rahnemoonfar - IEEE Journal of Selected Topics in …, 2022 - ieeexplore.ieee.org
Real-time semantic segmentation of aerial imagery is essential for unmanned ariel vehicle
applications, including military surveillance, land characterization, and disaster damage …

Panopticroad: Integrated panoptic road segmentation under adversarial conditions

H Sakaino - Proceedings of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Segmentation becomes one of the most important methods for scene understanding.
Segmentation plays a central role in recognizing things and stuff in a scene. Among all …

Flood extent and volume estimation using remote sensing data

G Popandopulo, S Illarionova, D Shadrin, K Evteeva… - Remote Sensing, 2023 - mdpi.com
Floods are natural events that can have a significant impacts on the economy and society of
affected regions. To mitigate their effects, it is crucial to conduct a rapid and accurate …

Efficient CNN-based disaster events classification using UAV-aided images for emergency response application

MH Bashir, M Ahmad, DR Rizvi, AAA El-Latif - Neural Computing and …, 2024 - Springer
Natural disasters can be unpredictable and catastrophic. Even after the event, the
repercussions are prolonged due to the incompetence of disaster management strategies …

CoWNet: A correlation weighted network for geological hazard detection

D Yin, B Zhang, J Yan, Y Luo, T Zhou, J Qin - Knowledge-Based Systems, 2023 - Elsevier
The geological hazard of landslide or debris flow is one of the most widespread causes of
mortality every year. Segmentation for them has been an effective tool to reduce the number …

Towards improved unmanned aerial vehicle edge intelligence: A road infrastructure monitoring case study

S Tilon, F Nex, G Vosselman, I Sevilla de la Llave… - Remote Sensing, 2022 - mdpi.com
Consumer-grade Unmanned Aerial Vehicles (UAVs) are poorly suited to monitor complex
scenes where multiple analysis tasks need to be carried out in real-time and in parallel to …

Development of an artificial neural network algorithm embedded in an on-site sensor for water level forecasting

CH Liu, TH Yang, OT Wijaya - Sensors, 2022 - mdpi.com
Extreme weather events cause stream overflow and lead to urban inundation. In this study, a
decentralized flood monitoring system is proposed to provide water level predictions in …