Gain mastery of image processing-based models with this project. You will work in a project team to work from the ground up to develop a full-functioning model to automate the process of car damage inspection for insurance claims and reporting using Computer Vision based techniques and Deep Learning
Problem Scenario :
Insurance firms often rely on care damage photos after an accident to conduct damage inspection as input for claims processing. This process can be tedious and time-consuming. This project provides an approach to leverage the power and speed of machine learning to efficiently inspect, assess and report on vehicle damage in the event of an accident
Aim :
This project aims to create mastery in candidates to utilize the power of deep learning and Convolutional Neural Networks (CNN ) to speed up the process of damage detection and evaluation to classify the type of car, type and severty of damage, and the location of the damage
Participants in this project will work in core teams to collect data and learn to implement data augmentation to improve model performance
What you will learn :
Computer Vision Project Organization
Data Requirements Design and data collection
Image data pre-processing and data augmentation techniques
Convolutional Neural Networks Design and Implementation
Model inferencing architecture
Requirements:
This project features JIT-based training in Python and image pre-processing and as such, candidates are not required to possess any skills in Python