3 papers
quant-ph2025
Potential of multi-anomalies detection using quantum machine learning
Takao Tomono, Kazuya Tsujimura
Maintenance of production equipment is critical in manufacturing. Typically, machine learning models are trained on sensor data closely attached to equipment. However, as the numbe…
quant-ph2025
Quantum Kernel Anomaly Detection Using AR-Derived Features from Non-Contact Acoustic Monitoring for Smart Manufacturing
Takao Tomono, Kazuya Tsujimura
The evolution of manufacturing toward smart factories has underscored major challenges in equipment maintenance, particularly the dependence on numerous contact sensors for anomaly…
quant-ph2024
Quantum kernel learning Model constructed with small data
Takao Tomono, Kazuya Tsujimura
We aim to use quantum machine learning to detect various anomalies in image inspection by using small size data. Assuming the possibility that the expressive power of the quantum k…