Correction to: Scientific Reports https://doi.org/10.1038/s41598-024-71775-8, published online 05 September2024
In the original version of this Article, Figures 5 and 8 contained editing marks that were not removed before publication. The original Figures 5 and 8 as well as their accompanying legends appear below.
Confusion matrix of different algorithms. SIR \(=-6\) dB. (a) CFAR, MFAP set to \({10}^{-6}\). (b) FCN. (c) LR-ASPP. (d) MobileNetV2. (e) ResNet-101. (f) Xception. (g) JSLCNN. (h) AC-UNet. (i) LDNet.
Results of RFI detection for out-of-dataset SIR. (a) Time–frequency spectrogram with SIR = 5 dB. (b) Detection results with SIR = 0 dB. (c) Detection results with SIR = 5 dB. (d) Detection results with SIR = 10 dB.
In addition, in Table 3, the “Comparison of MIoU (%)” for “LDNet” was incorrectly given as “–”. The incorrect and correct values appear below.
Incorrect:
Algorithm | MIoU | Comparison of MIoU (%) | FNR \(\times {10}^{-4}\) | FPR \(\times {10}^{-4}\) |
|---|---|---|---|---|
LDNet | 0.9722 | – | 1.61 | 0.33 |
Correct:
Algorithm | MIoU | Comparison of MIoU (%) | FNR \(\times {10}^{-4}\) | FPR \(\times {10}^{-4}\) |
|---|---|---|---|---|
LDNet | 0.9722 | ------ | 1.61 | 0.33 |
The original Article has been corrected.
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Zheng, F., Zhang, Z. & Zhang, D. Author Correction: Lightweight deep neural network for radio frequency interference detection and segmentation in synthetic aperture radar. Sci Rep 14, 25390 (2024). https://doi.org/10.1038/s41598-024-75441-x
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DOI: https://doi.org/10.1038/s41598-024-75441-x
