O. F. Beyca Et Al. , "Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory," IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , vol.13, no.2, pp.1033-1044, 2016
Beyca, O. F. Et Al. 2016. Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , vol.13, no.2 , 1033-1044.
Beyca, O. F., RAO, P. K., KONG, Z., BUKKAPATNAM, S. T. S., & KOMANDURI, R., (2016). Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , vol.13, no.2, 1033-1044.
Beyca, Ömer Et Al. "Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory," IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , vol.13, no.2, 1033-1044, 2016
Beyca, Ömer F. Et Al. "Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory." IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , vol.13, no.2, pp.1033-1044, 2016
Beyca, O. F. Et Al. (2016) . "Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory." IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , vol.13, no.2, pp.1033-1044.
@article{article, author={Ömer Faruk Beyca Et Al. }, title={Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory}, journal={IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING}, year=2016, pages={1033-1044} }