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PANNs

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Safetensors
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PANNs (models)

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  1. models/pretrained/Cnn10_mAP=0.380.pth +3 -0
  2. models/pretrained/Cnn14_16k_mAP=0.438.pth +3 -0
  3. models/pretrained/Cnn14_8k_mAP=0.416.pth +3 -0
  4. models/pretrained/Cnn14_DecisionLevelAtt_mAP=0.425.pth +3 -0
  5. models/pretrained/Cnn14_DecisionLevelMax_mAP=0.385.pth +3 -0
  6. models/pretrained/Cnn14_emb128_mAP=0.412.pth +3 -0
  7. models/pretrained/Cnn14_emb32_mAP=0.364.pth +3 -0
  8. models/pretrained/Cnn14_emb512_mAP=0.420.pth +3 -0
  9. models/pretrained/Cnn14_mAP=0.431.pth +3 -0
  10. models/pretrained/Cnn6_mAP=0.343.pth +3 -0
  11. models/pretrained/DaiNet19_mAP=0.295.pth +3 -0
  12. models/pretrained/LeeNet11_mAP=0.266.pth +3 -0
  13. models/pretrained/LeeNet24_mAP=0.336.pth +3 -0
  14. models/pretrained/MobileNetV1_mAP=0.389.pth +3 -0
  15. models/pretrained/MobileNetV2_mAP=0.383.pth +3 -0
  16. models/pretrained/Res1dNet31_mAP=0.365.pth +3 -0
  17. models/pretrained/Res1dNet51_mAP=0.355.pth +3 -0
  18. models/pretrained/ResNet22_mAP=0.430.pth +3 -0
  19. models/pretrained/ResNet38_mAP=0.434.pth +3 -0
  20. models/pretrained/ResNet54_mAP=0.429.pth +3 -0
  21. models/pretrained/Wavegram_Cnn14_mAP=0.389.pth +3 -0
  22. models/pretrained/Wavegram_Logmel_Cnn14_mAP=0.439.pth +3 -0
  23. models/pretrained/paper_statistics.zip +3 -0
  24. models/pretrained/source.txt +1 -0
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