• Gaurav Gunjal
• Harshada Sapkal
• Pooja Kulkarni
• Snehalata Nandanwar

Vehicle insurance claiming is an important area in vehicle industry. In this paper, we consider the problem of damage identification and damage classification of the various parts of the car. For this, we explore various deep learning techniques through which we can achieve image processing for damage identification, like Convolutional Neural Network and Transfer Learning. Initially, we test the accuracy of both the techniques with same amount of training image dataset. Experimental results show that transfer learning works better than convolutional neural network. Then we work for various techniques viz. fetching car and its owner information from RTO which can eliminate frauds. After that, insurance cost of each part will be shown to user and all the generated data will be reflected in a pdf file.

deep learning, convolutional neural network, transfer learning

"Car Damage Analysis and Insurance Claim System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.36-39, April-2019, Available :http://www.jetir.org/papers/JETIR1904708.pdf

"Car Damage Analysis and Insurance Claim System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp36-39, April-2019, Available at : http://www.jetir.org/papers/JETIR1904708.pdf