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Computer Vision-based Characterization of Large-scale Jet Flames using a Synthetic Infrared Image Generation Approach
The results suggest that it is possible to realistically replicate the results for experiments carried out using both visible and infrared cameras.
Experimental Large-Scale Jet Flames' Geometrical Features Extraction for Risk Management Using Infrared Images and Deep Learning Segmentation Methods
This research work explores the application of deep learning models in an alternative approach that uses the semantic segmentation of jet fires flames to extract main geometrical attributes, relevant for fire risk assessments.
Comparing Machine Learning based Segmentation Models on Jet Fire Radiation Zones
One such characterization would be the segmentation of different radiation zones within the flame, so this paper presents an exploratory research regarding several traditional computer vision and Deep Learning segmentation approaches to solve this specific problem.
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