Published March 13, 2025 | Version v1
Software Open

Top-k Bottom All but σ Loss Strategy for Medical Image Segmentation

Authors/Creators

  • 1. University Politehnica of Bucuresti
  • 2. University Politehnica of Bucharest

Description

Code for the proposed methodology

Files

Code_Python_Top_Bottom_Share.zip

Files (64.7 kB)

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md5:0a64ed6a278cec2fa744822c5020dd27
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Additional details

Identifiers

Other
TBD

Related works

Is part of
Software: TBD (Other)

Dates

Submitted
2025-03-13

Software

Development Status
Active

References

  • Lapin, M., Hein, M., Schiele, B., 2016. Loss functions for top-k error: Analysis and insights, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1468-1477
  • Lyu, S., Fan, Y., Ying, Y., Hu, B.G., 2020. Average top-k aggregate loss for supervised learning. IEEE Transactions on Pattern Analysis and Machine Intelligence 44, 76-86