scholarly journals Automatic tool segmentation and tracking during robotic intravascular catheterization for cardiac interventions

2021 ◽  
Vol 11 (6) ◽  
pp. 2688-2710
Author(s):  
Olatunji Mumini Omisore ◽  
Wenke Duan ◽  
Wenjing Du ◽  
Yuhong Zheng ◽  
Toluwanimi Akinyemi ◽  
...  
2020 ◽  
Vol 68 (4) ◽  
pp. 283-293
Author(s):  
Oleksandr Pogorilyi ◽  
Mohammad Fard ◽  
John Davy ◽  
Mechanical and Automotive Engineering, School ◽  
Mechanical and Automotive Engineering, School ◽  
...  

In this article, an artificial neural network is proposed to classify short audio sequences of squeak and rattle (S&R) noises. The aim of the classification is to see how accurately the trained classifier can recognize different types of S&R sounds. Having a high accuracy model that can recognize audible S&R noises could help to build an automatic tool able to identify unpleasant vehicle interior sounds in a matter of seconds from a short audio recording of the sounds. In this article, the training method of the classifier is proposed, and the results show that the trained model can identify various classes of S&R noises: simple (binary clas- sification) and complex ones (multi class classification).


2009 ◽  
Vol 3 (2) ◽  
pp. 117-128
Author(s):  
Ming Cong ◽  
Dong Liu ◽  
Jing Liu
Keyword(s):  

2001 ◽  
Vol 16 (10) ◽  
pp. 949-962 ◽  
Author(s):  
Işıl Celasun ◽  
A.Murat Tekalp ◽  
Mete H Gökçetekin ◽  
Derin M Harmancı

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