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.
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About Vijay Raghani
Vijay Raghani has 13 years of professional experience with 4 years in Architect role covering all aspects of software life cycles. He is a Sr. Architect for MS Stack (SharePoint and Office 365 technologies) in Sogeti India Microsoft Practice and Innovation Lead in Sogeti India for upcoming technologies such as 'AI' (Chatbots, Cognitive Services and Artificial Intelligence). He has been involved in Solution Estimation, RFP response for SharePoint projects across various industry verticals.
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