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In this paper, the research area has always been car price forecasting. We demonstrate that using the proposed object detection method, the type of damage can be categorized into two classes with good accuracy damaged and undamaged. So, when we discovered these issues, we decided to develop a mobile application called Car Price Prediction, which allows users to anticipate the price of a used car. So, we trained the damage identification model using our data using a state-of-the-art image detection method convolutional neural network and evaluated the accuracy on a GPU server and a smartphone.

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