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Table 5.
Comparison between smoothing techniques.
| Method | Sen | Spe | Acc |
|---|---|---|---|
| (%) | (%) | (%) | |
| Median + Lerr | 81 | 99 | 90 |
| Cosine + Lerr | 92 | 90 | 91 |
| Hamming + Lerr | 93 | 81 | 87 |
| Gaussian + Lerr | 92 | 88 | 90 |
| No prefilter + Lerr + Ltv | 94 | 97 | 96 |
Notes. The first four rows show performance results obtained by applying smoothing (with different kernels) before the CNN using Lerr to train the network. The last row presents the performance metrics of CNN with the loss function (Eq. (4)) without smoothing. Data set 1 was used.
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