Designing CNN Neural Network Model for Detecting Fractures of Lower Extremities by X-ray Images
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2024
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The problem of using CNN neural network model for detecting fractures of lower extremities by X-ray images was investigated. In particular, the Dense Convolutional Network architecture is used, which is one of the advanced convolutional neural networks, which is well suited for the task of identifying bone fractures in X-ray images due to its efficiency and ability to store information at all levels of the network. It differs from traditional CNNs in that each layer is connected to all previous layers, which allows storing information and facilitates the transfer of gradients during training. Regarding the advantages of DenseNet over other networks, it has fewer parameters compared to others, which reduces the need for computing resources. Also improved feature retention, where the model better remembers and uses features from earlier layers, improving its ability to recognize small details important for fracture detection.
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Kharysh I., Sobko O., Mazurets O. Designing CNN Neural Network Model for Detecting Fractures of Lower Extremities by X-ray Images. The Impact of Scientific Research on the Development of the Modern World. Proceedings of the XLІV International scientific and practical conference. October 23-25, 2024. Dubrovnik, Croatia. 2024. Pp. 91-96