Seung-Yeon Hwang1, Jeong-Joon Kim2,*
CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2649-2663, 2022, DOI:10.32604/cmc.2022.022593
Abstract Artificial intelligence, which has recently emerged with the rapid development of information technology, is drawing attention as a tool for solving various problems demanded by society and industry. In particular, convolutional neural networks (CNNs), a type of deep learning technology, are highlighted in computer vision fields, such as image classification and recognition and object tracking. Training these CNN models requires a large amount of data, and a lack of data can lead to performance degradation problems due to overfitting. As CNN architecture development and optimization studies become active, ensemble techniques have emerged to perform image classification by combining features extracted… More >
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