Vehicle Damage Inspection Modeling [Ref: TT10070]

ENROLLING COHORT 4 NOW!!

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