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Ensemble of Multi-View Learning Classifiers for Cross-Domain Iris Presentation Attack Detection

Python 61.49% MATLAB 0.04% Shell 0.14% C++ 0.60% C 0.01% Objective-C 37.61% Makefile 0.07% Dockerfile 0.05%

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emvlc-ipad's Issues

Test only

Sorry to bother you. And thanks for providing the algorithms and pretrained models.

But I don't really understand the code structure now.

Is <summarize_accuracy.py> I should use for testing pretrained models only? I got No such file or directory:...error when implementing it. That seems like I don't have a .csv file.

Could you please tell me how to test the pretrained models only?
Thanks again.

Testing the pre-trained model

Hello,
Thanks for sharing your code. I would like to test your code using pre-trained model on my dataset. Do you have a code that simply take an image and identify it as spoof or live.
I highly appreciate you if you can help me with this or gave me some hints how I can use the pre-trained models¿

Pretrained model

Hi, thanks for providing the code. I am interesting in your paper and the method to solve the problem. Is there anyway I can get the pretrained model? I don't have the computer power and datasets to train the entire model but I want to test in the LivDet2017 DataSet. Would you please give me the pre-trained model?

bsifcpp compilation

Hi, thanks for providing the code. Could you provide more detailed instructions on how to compile bsifcpp from beginning? What are the required libraries to be installed first? Also, the absolute path makes it difficult to understand the library path.

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