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Car Damage Detection with Deep Learning Algorithms
Our client is an international car rental company. Upon return, the vehicles are manually inspected for damages by experts.
Problem
Damage control and related cost calculations are being performed by experts.
Due to the increase of fleet and inspection quantity, alternative solutions are required for cost and time optimization
Action
Developed an AI algorithm to replace experts and their manual controls.
Combined two models (1. part detection 2. damage detection) to predict required replacements and repairs.
Integrated with third party to obtain up to date spare part costs
Tool Stack
Azure, Python, Rabbit MQ, .NET, SQL DB, Vue.js, Pytorch, Tensorflow
95
%
Accuracy rate for detection
400
%
Increase process cycle
85
%
Automation