In this research, we propose to replace the traditional methods of vehicle damage inspection (for car insurance) with a Machine Learning based automated solution.
Deep Learning based models are used to recognize whether a car in a given image is damaged and its type/severity. A promising attempt in classifying car damages into multiple classes is presented. The emphasis is on fine-tuning this model iteratively with the objective of achieving satisfactory accuracy scores.
This research open doors for future collaborations on image recognition projects in general and for the car insurance field in particular by enabling insurers to assess customer vehicle damage and expedite claims settlement.
Download the report here.