This paper proposes a classification method using Convolutional Neural Network(CNN) to classify the types of a truck. The images of the vehicle from the camera are classified according to the vehicle type and the cargo compartment. Those data are used as training data. To training the neural networks with supervised learning, the appropriate CNN structure is designed and classified images and correct output results are presented to train the weights of neural networks. When the actual image is input, the output of CNN can be used to distinguish whether the loading part of a truck is the covered or not. Experimental results show that images can be classified according to car type and loading type of cargo and it can be used for the pre-classification of loading defect inspection.
CITATION STYLE
Lee, D. G. (2019). Classification of the loading type of Trucks using convolutional neural network. International Journal of Innovative Technology and Exploring Engineering, 8(4S2), 79–82.
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