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After successfully running the MNIST classifier example on the ZCU104 board, I wanted to try running a hybrid CNN-SVM model
using the extracted features of all the test samples ( the output features of the MNIST classifier example) to be used as training and test examples for the SVM classifier using PYNQ-DPU
as shown in the code below.
However, the obtained accuracy of this model was about 34.34.% compared to CNN model provided in the MNIST classifier example (98.61%)
After successfully running the MNIST classifier example on the ZCU104 board, I wanted to try running a hybrid CNN-SVM model
using the extracted features of all the test samples ( the output features of the MNIST classifier example) to be used as training and test examples for the SVM classifier using PYNQ-DPU
as shown in the code below.
However, the obtained accuracy of this model was about 34.34.% compared to CNN model provided in the MNIST classifier example (98.61%)
I don't get what's the reason for this bad accuracy. Any help please?
Thanks
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