Open AccessPreventing Car Damage using CNN and Computer Vision
Author(s) -
Dr.Avinash Sharma*,
Aaditi Verma,
Dhananjay Gupta
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a5020.119119
Subject(s) - convolutional neural network , computer science , triage , artificial intelligence , task (project management) , object (grammar) , process (computing) , transfer of learning , computer vision , deep learning , cognitive neuroscience of visual object recognition , machine learning , engineering , medicine , systems engineering , medical emergency , operating system
This research contain convolutional neural network are used to recognize whether a car on a given image is damage or not, from where it is damage and severity of the damage. Using transfer learning to take advantage of available models that are trained on a more general object recognition task, very satisfactory performance has been achieved, which indicate great opportunities of this approach. Car accidents are stressful and the auto claims process is ripe for disruption. Using computer vision to accurately classify vehicle damage and facilitate claims triage