Table 2 The results of each sample based on convolutional neural networks
From: Diagnosis of left ventricular hypertrophy using convolutional neural network
Sample no. | Number of potential Windows after filtering | Coarse positioning time /s | Effective positioning(Y/N) |
|---|---|---|---|
No.1 | 18 | 11.04 | Y |
No.2 | 52 | 30.02 | Y |
No.3 | 43 | 26.86 | Y |
No.4 | 63 | 38.00 | Y |
No.5 | 56 | 31.64 | Y |
No.6 | 29 | 20.92 | Y |
No.7 | 26 | 15.25 | Y |
No.8 | 64 | 41.03 | Y |
No.9 | 94 | 52.66 | Y |
No.10 | 49 | 32.00 | Y |