転移学習による出土銭貨の画像認識

抄録

Recently, AI technology called deep learning has been attracting attention. Deep learning is a kind of neural network. It is a method of machine learning using a hierarchical neural network with a multi-layer structure. Deep learning has shown great results in image recognition. In this study, we consider the classification of unearthed coins using deep learning. There are many types of unearthed coins to be excavated from a ruin. One of the most famous coins is Kanei-tsuho coins. There are many subdivisions of Kanei-tsuho coins. However, the classification of unearthed coins is even difficult task for numismatics experts.
In this research, we use transfer learning to classify unearthed coins. Transfer learning is a type of machine learning. This method acquires knowledge through separate training data. Use the acquired knowledge to classify other data. We will verify whether unearthed coins can be classified using a model learned from large-scale image data.