My PhD dissertation is an interdisciplinary study that combines Korea studies with computer vision. The research focuses on three different case studies that employ various aspects of computer vision, namely classification, object detection, and OCR. An example of these is the case study examining the rise of modern Korean print culture during the 1920s. This era marked a significant period of growth in book, newspaper, and magazine production, and print shops played a vital role. I employ a Convolutional Neural Network (CNN) to classify the print shops of books published in colonial Korea, allowing for a quantitative analysis of this period.