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Object detection and identification is a challenging area of computer visionand a fundamental requirement for autonomous cars. This project aims to jointlyperform object detection of a swap-body and to find the type of swap-body byreading an ILU code using an efficient optical character recognition (OCR)method. Recent research activities have drastically improved deep learningtechniques which proves to enhance the field of computer vision. Collectingenough images for training the model is a critical step towards achieving goodresults. The data for training were collected from different locations withmaximum possible variations and the details are explained. In addition, dataaugmentation methods applied for training has proved to be effective inimproving the performance of the trained model. Training the model achievedgood results and the test results are also provided. The final model was testedwith images and videos. Finally, this paper also draws attention to some of themajor challenges faced during various stages of the project and the possiblesolutions applied.

Object Detection and Recognition of Swap-Bodies using Camera mounted on a Vehicle