Damage parameter estimation for ancient DNA

Flood mapping and damage assessment in GEE

3DAeroRelief is a high-resolution 3D point cloud benchmark dataset designed for semantic segmentation in post-disaster scenarios. It includes 3D data for eight distinct areas, COLMAP configuration files for reconstruction, and Python utility scripts for merging and processing semantic labels and geometry.

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

This repository provides a tutorial and code for reproducing the data and results presented in the following publication: Automated Mapping of Post-Storm Roof Damage Using Deep Learning and Aerial Imagery: A Case Study in the Caribbean (Kucharczyk, Nesbit, & Hugenholtz, 2025, Remote Sensing).

Sheldon K. Salmon — AI Reliability Architect. Creator of the AION Constitutional Stack and the CERTUS certainty‑engineering methodology. He designed, directed, and red‑teamed VERITAS — applying epistemic scoring, Uncertainty Mass, and permanent STP seals to community crisis data. Code is open source. The judgment is not.

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

A Structured Prompting Framework for the Proportional Assessment of Non-Pecuniary Damages

An AI-powered web application that analyzes vehicle images to detect damage, estimate severity, and suggest repair costs using a vision-language model.

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

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

Predicting building damage from the 2015 Nepal Gorkha earthquake using ensemble ML models (XGBoost, LightGBM), explainable AI (SHAP), and MLflow tracking

KML File and script to generate the file to show the official damage assessment from CAL FIRE for the 2025 Palisades Fire for use with Google Earth Pro, possibly other GIS software too.