An advanced AI-driven approach to burned surface quantification in fire performance testing of wood materials

This collection contains data obtained during flammability tests of diffrent wood-based materials used to train ai models for matching burn area.The data was recorded using a test stand equipped with a burner mounted on a guide controlled by a stepper motor and a USB camera. The entire setup was controlled by an ESP32 microcontroller and dedicated software.ZIP files contains masks:mask - original CV generated masks, used to generate ai model (train_cv.pt),manual - manual corrected masks, used to generate ai model (train_manual),ai-cv - masks generated by ai model based on CV generated masks,ai-manual - masks generated by ai model based on manually corrected masks.cpp/py files (also in train_software.zip) - software versions used in data generating, testing and analysing process.pt files - generated models.png files - samples of masks.

Authors

Institutions

Publication Details

Journal
Wood Material Science and Engineering
Published
2026-09-10
DOI
https://doi.org/10.1080/17480272.2026.2729534
Primary Topic
Fire dynamics and safety research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

An advanced AI-driven approach to burned surface quantification in fire performance testing of wood materials

Anita Wronka, Patryk Maciej Król, Grzegorz Kowaluk
Wood Material Science and Engineering
Fire dynamics and safety research
article

An advanced AI-driven approach to burned surface quantification in fire performance testing of wood materials

Anita Wronka, Patryk Maciej Król, Grzegorz Kowaluk
article en

Abstract

This collection contains data obtained during flammability tests of diffrent wood-based materials used to train ai models for matching burn area.The data was recorded using a test stand equipped with a burner mounted on a guide controlled by a stepper motor and a USB camera. The entire setup was controlled by an ESP32 microcontroller and dedicated software.ZIP files contains masks:mask - original CV generated masks, used to generate ai model (train_cv.pt),manual - manual corrected masks, used to generate ai model (train_manual),ai-cv - masks generated by ai model based on CV generated masks,ai-manual - masks generated by ai model based on manually corrected masks.cpp/py files (also in train_software.zip) - software versions used in data generating, testing and analysing process.pt files - generated models.png files - samples of masks.

Wood Material Science and Engineering
Warsaw University of Life Sciences (PL)
Openalex Percentile: Top 87%
Fire dynamics and safety research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

An advanced AI-driven approach to burned surface quantification in fire performance testing of wood materials — Anita Wronka, Patryk Maciej Król, et al. · Wood Material Science and Engineering (2026) | TGRS Research Map | TGRS