CNN Approach for Car Damage Detection in Insurance Claims

CNN Approach for Car Damage Detection in Insurance Claims

Prof. Soniya Dhotre1, Kushal Agrawal2, Shardul Potdar3 , Preetam Patil4
1Prof. Soniya Ravindra Dhotre, Computer Engineering, Sinhgad Academy of Engineering 2Kushal Manoj Agrawal, Computer Engineering, Sinhgad Academy of Engineering 3Shardul Surendra Potdar, Computer Engineering, Sinhgad Academy of Engineering 4Preetam Babaso Patil, Computer Engineering, Sinhgad Academy of Engineering

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ABSTRACT

The automotive industry is witnessing a growing demand for advanced safety and maintenance systems to enhance vehicle safety and reduce maintenance costs. Car damage detection plays a pivotal role in achieving these objectives. This abstract provides an overview of the concept of car damage detection, its importance, and the technologies and methodologies involved. Car damage detection refers to the process of identifying and assessing physical damage to a vehicle, such as dents, scratches, cracks, or structural deformities. It is essential for various stakeholders, including car owners, insurance companies, and automotive service providers, as it enables timely repair and maintenance, facilitates insurance claims, and ensures road safety.

Key Words:     CNN, Mask R-CNN, Image Analysis, Computer Vision, Machine Learning, Deep-Learning