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Title: :  Car Exterior Damage Detection Using Mask R-CNN
PaperId: :  11563
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 6 Issue 2 2020
DUI:    16.0415/IJARIIE-11563
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Pradhip Kumar.RSRM Valliammai Engineering College
Sanjeev Kumar PatelSRM Valliammai Engineering College
ShankarSRM Valliammai Engineering College
Ms.C.PabithaSRM Valliammai Engineering College

Abstract

Computer Science and Engineering
Car Exterior Damage Classification,CNN,Transfer Learning,Convolutional Auto-encoders,Mask R-CNN
Recently, the production of image-based vehicle insurance is an important area with considerable scope for automation reach. In this paper we consider the issue of classifying car damage, where some of the categories may be fine-granular. To this reason, we are exploring deep learning-based techniques. Initially we try to train a CNN directly with a collection of training data. However, it's not working well due to a small collection of labeled data. Hence, we investigate the domain-specific pre-training effect accompanied by fine-tuning with a large number of annotated training-data. As Faster R-CNN and SVM have not identified damaged cars with high accuracy, and the Cascade R-CNN takes an immense amount of time to train and check the data that we are working on to fit. Hence, we are training data into a R-CNN Mask that produces adequate results compared to traditional Neural Networks. Though there is a lot of unknowns such as partial images, Hence the classifier was built to detect amorphous damages. The model is layered over 3 classifications of detecting the car and examining whether the damage dealt is high or low. Finally, the classifier is projected with the flask environment to make the working experience easier, since it runs on a localhost the compile time does not exceed 5 seconds irrespective of the quality of the image. Experimental results indicate that Mask R-CNN works better than convolutional R-CNN as transfer learning works better than domain specific fine-tuning such as Cascade and Faster R-CNN. We achieve 89.5 per cent accuracy with Mask R-CNN through transfer combination.

Citations

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IJARIIE Pradhip Kumar.R, Sanjeev Kumar Patel, Shankar, and Ms.C.Pabitha. "Car Exterior Damage Detection Using Mask R-CNN" International Journal Of Advance Research And Innovative Ideas In Education Volume 6 Issue 2 2020 Page 862-868
MLA Pradhip Kumar.R, Sanjeev Kumar Patel, Shankar, and Ms.C.Pabitha. "Car Exterior Damage Detection Using Mask R-CNN." International Journal Of Advance Research And Innovative Ideas In Education 6.2(2020) : 862-868.
APA Pradhip Kumar.R, Sanjeev Kumar Patel, Shankar, & Ms.C.Pabitha. (2020). Car Exterior Damage Detection Using Mask R-CNN. International Journal Of Advance Research And Innovative Ideas In Education, 6(2), 862-868.
Chicago Pradhip Kumar.R, Sanjeev Kumar Patel, Shankar, and Ms.C.Pabitha. "Car Exterior Damage Detection Using Mask R-CNN." International Journal Of Advance Research And Innovative Ideas In Education 6, no. 2 (2020) : 862-868.
Oxford Pradhip Kumar.R, Sanjeev Kumar Patel, Shankar, and Ms.C.Pabitha. 'Car Exterior Damage Detection Using Mask R-CNN', International Journal Of Advance Research And Innovative Ideas In Education, vol. 6, no. 2, 2020, p. 862-868. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Car_Exterior_Damage_Detection_Using_Mask_R_CNN_ijariie11563.pdf (Accessed : 06 September 2022).
Harvard Pradhip Kumar.R, Sanjeev Kumar Patel, Shankar, and Ms.C.Pabitha. (2020) 'Car Exterior Damage Detection Using Mask R-CNN', International Journal Of Advance Research And Innovative Ideas In Education, 6(2), pp. 862-868IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Car_Exterior_Damage_Detection_Using_Mask_R_CNN_ijariie11563.pdf (Accessed : 06 September 2022)
IEEE Pradhip Kumar.R, Sanjeev Kumar Patel, Shankar, and Ms.C.Pabitha, "Car Exterior Damage Detection Using Mask R-CNN," International Journal Of Advance Research And Innovative Ideas In Education, vol. 6, no. 2, pp. 862-868, Mar-App 2020. [Online]. Available: https://ijariie.com/AdminUploadPdf/Car_Exterior_Damage_Detection_Using_Mask_R_CNN_ijariie11563.pdf [Accessed : 06 September 2022].
Turabian Pradhip Kumar.R, Sanjeev Kumar Patel, Shankar, and Ms.C.Pabitha. "Car Exterior Damage Detection Using Mask R-CNN." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 6 number 2 (06 September 2022).
Vancouver Pradhip Kumar.R, Sanjeev Kumar Patel, Shankar, and Ms.C.Pabitha. Car Exterior Damage Detection Using Mask R-CNN. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2020 [Cited : 06 September 2022]; 6(2) : 862-868. Available from: https://ijariie.com/AdminUploadPdf/Car_Exterior_Damage_Detection_Using_Mask_R_CNN_ijariie11563.pdf
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