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An Object Detection Algorithm for Anomaly Detection
- Author(s)
- 백재훈
- Alternative Author(s)
- JAEHUN BAEK
- Advisor
- 신동욱
- Department
- 일반대학원 수학과
- Publisher
- The Graduate School, Ajou University
- Publication Year
- 2023-08
- Language
- eng
- Keyword
- Anomaly detection; Object detection; Oral image
- Alternative Abstract
- In this thesis, an anomaly detection algorithm is applied to a mobile oral health care application. Particularly, one class YOLOv3 has been investigated as an anomaly detection model to classify pictures of mouths, which will serve as inputs for subsequent machine learning models. Outstanding performance has been achieved by proposing appropriate annotation strategies for the datasets and modifying the loss function. Notably, the model can classify not only oral and non-oral pictures but also output preprocessed pictures that only contain the area around the lips by using the predicted bounding box. Thus, the model performs both prediction and preprocessing simultaneously.
- Fulltext
- Appears in Collections:
- Graduate School of Ajou University > Department of Mathematics > 3. Theses(Master)
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