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Performance testing #3

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LeTrungLinh opened this issue May 22, 2024 · 3 comments
Open

Performance testing #3

LeTrungLinh opened this issue May 22, 2024 · 3 comments

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@LeTrungLinh
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Thank you for your research. i also retrain your model with your config on GTX3090ti on COVID-QU-Ex dataset (3728:932:1166 for Train:Val:Test), but it's give a really high performance than the table in your paper. Can you help me to verify my confusion:

dice0.9807 _miou0.9629 _pre0.9718 _recall0.9702 _f1_score0.9704 _pa0.9866

@FDG2801
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FDG2801 commented Sep 6, 2024

hi, can you tell me how did you manage to run the covid dataset? I'm having problems with the type of files. Should I use the txt for validation? what about training?

@LeTrungLinh
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Hi friend, I just use the model file of CoTrFuse. For manage the covid dataset, i just put it in separate folder and process it by Dataset code that use can implement by yourself.

@BinYCn
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BinYCn commented Sep 11, 2024

It sounds like the performance discrepancy might stem from differences in how evaluation metrics are being computed.

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3 participants