Professor Hsiang-Chen Wang is currently a professor at the Department of Mechanical Engineering, and the Institute of Opto-Mechatronics Engineering, National Chung Cheng University (CCU). At the same time, he serves as the vice president for R&D and the director of the Center of Technology Promotion at CCU; He is also an adjunct professor at the Department of Post Baccalaureate Medicine, Kaohsiung Medical University.

The early detection of esophageal cancer presents a considerable difficulty, which contributes to its high prevalence as a major cause of cancer-related fatalities. This project will utilize various machine learning models, including YOLOv5, YOLOv8, R-CNN, and Faster R-CNN, to predict and detect early-stage esophageal cancer. It will make use of two models of esophageal cancer images: the white-light images (WLI) model and the hyperspectral narrowband images (HSI-NBI) model. These models will be generated through a conversion algorithm referred to as the spectrum-aided vision enhancer (SAVE). The main goal will be to discover Dysplasia and Squamous Cell Carcinoma (SCC). The evaluation of model performance will be conducted using the created confusion matrix and five important indicators: precision, recall, F1-score, mAP, and the confusion matrix of the trained model.