상세정보
학술대회
Sound-based Anomaly Detection Using a Locally Constrained Capsule Network
- 발행일
- 202110
- 출처
- International Conference on Information and Communication Technology Convergence (ICTC) 2021, pp.1-3
- 협약과제
- 21ZK1100, 호남권 지역산업 기반 ICT 융합기술 고도화 지원사업, 이길행
- 초록
- In this study, we propose a new technique for abnormal acoustic diagnosis based on a locally constrained capsule network architecture. The newly designed anomaly diagnosis capsule network simplifies the learning network by removing auxiliary layers, and reduces computation by minimizing the operation between capsule layers. When compared with those of other network models utilized for abnormality diagnosis, the accuracy, area under the curve, and F1-score of the proposed model were sufficient.
- KSP 제안 키워드
- Abnormality diagnosis, Acoustic diagnosis, F1-score, Learning network, Network Architecture, Network model, Proposed model, anomaly detection, area under the curve(AUC)