Damage parameter estimation for ancient DNA

Flood mapping and damage assessment in GEE

This repository houses a comprehensive deep learning-based system for the scene classification of very high-resolution satellite imagery, focusing on post-earthquake damage assessment. The primary case study involves the devastating earthquakes that occurred in Kahramanmaraş province, Türkiye, in 2023.

MATLAB code to generate some results on the paper (Kitayama, & Cilsalar, 2022).

Building machine learning models that predict the damage level caused by an earthquake on a building using the Nepal's Earthquake dataset

Multi-Head Convolutional Networks for Post Earthquake Damage Assessment of Damaged Buildings

Guided Team Challenge 2021: Exposure Team Project

Post-Disaster Damage Assessment

AIM Group® Worldwide is an third party inspection and 3rd maritime professional specialists group independent acting globally in close to 100 countries.

AIMGroup is marine cargo ship surveyors and consultant with expertise on class and risk managing on seaworthiness and tecnical condition.

The study uses YOLO models on satellite imagery to detect collapsed buildings in Antakya after the 2023 Türkiye earthquake, achieving good results with YOLOv7 but highlighting challenges.

Geospatial analysis of flood impacts in Somalia, using GIS and spatial statistics.

This repository provides the SeAn-CP method, a semi-analytical algorithm for efficiently calculating critical plane factors in fatigue analysis. Compatible with finite element analysis, it handles complex geometries and loading conditions, offering a faster alternative to traditional plane scanning with similar accuracy.