Generative adversarial networks review in earthquake-related engineering fields

GC Marano, MM Rosso, A Aloisio… - Bulletin of Earthquake …, 2024 - Springer
Within seismology, geology, civil and structural engineering, deep learning (DL), especially
via generative adversarial networks (GANs), represents an innovative, engaging, and …

PDD: Post-Disaster Dataset for Human Detection and Performance Evaluation

H Song, W Song, L Cheng, Y Wei… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Human detection is aimed at automatically labeling specific semantic objects in high-
resolution images, which is a key problem in the post-disaster search and rescue (SAR) …

ATR HarmoniSAR: A System for Enhancing Victim Detection in Robot-assisted Disaster Scenarios

S Mahmud, AA Fime, JH Kim - IEEE Access, 2024 - ieeexplore.ieee.org
As our world increasingly faces various disastrous events, there is an urgent need for
improved methods of disaster response, particularly for the detection of victims trapped in …

[PDF][PDF] The MAX Drone for Autonomous Indoor Exploration

G Tolt, J Rydell, M Tulldahl, M Holmberg… - … Systems for Crisis …, 2023 - idl.iscram.org
This paper presents the concept and prototype implementation of a drone for Multi-purpose
Autonomous eXploration of indoor environments–MAX. The purpose of MAX is to support …

Enhancing Post-Disaster Survivor Detection Using UAV Imagery and Transfer Learning Strategies

N Ahmed, S Al-Maadeed - 2024 International Wireless …, 2024 - ieeexplore.ieee.org
In disaster response and search and rescue operations, the immediate detection of survivors
remains a critical challenge. This research pioneers a novel approach to rapidly detect …