@article{M329AA7B2,
title = "A Method of the Breast Cancer Image Diagnosis Using Artificial Intelligence Medical Images Recognition Technology Network",
journal = "The Journal of Korean Institute of Communications and Information Sciences",
year = "2023",
issn = "1226-4717",
doi = "10.7840/kics.2023.48.2.216",
author = "Daewon Kwak, Jiwoo Choi, Sungjin Lee",
keywords = "Breast cancer, Image recognition, segmentation, Classification",
abstract = "The recent advance of image recognition technology comes from the accumulation of numerous data and deepening of neural network. However, training these various data on a deep neural network causes various problems. Overfitting caused by a small amount of data, class imbalance resulting from the difference in the amount of data between classes, and multi-class training problems. This paper found and analyzed these problems occurring in such small data sets, and suggested solutions and analyzed the performance through experiments. For these goals, we compared open small data sets and the differences between them and selected the training techniques that perform well for each dataset."
}