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IEEE/ICACT20230153 Slide.03        [Big Slide]	Oral Presentation
	The image data is used as the input value of the Neural Network model by loading normal data and abnormal data from the dataset constructed through the extraction process from Heunginjimun CCTV images. As a Neural Network model for the classification task, four types of pre-trained-based Deep Learning models, EfficientNetB0, EfficientNetB2, ShuffleNet_v2, and AlexNet, were used. Figure 1 is a structured picture of the overall architecture of Heunginjimun roof tilt detection. The dataset used for pre-learning is ImageNet [8]. When the image of the dataset generated from Heunginjimun CCTV is input into the model, the image is readjusted according to the input size of each model. Then the model's feature extraction and classification parts are classified into normal and abnormal classes.

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