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The official implementation of the 2pCePd-Net model. pBPf Fusion block coming soon...

Project description

This is the official Pytorch implementation of 2pCePd-Net model published in IEEE Transactions on Instrumentation and Measurement

DOI: 10.1109/TIM.2025.3569005

Model Sample Usage Code:

from two_pcepd import model

network, optimizer = model.create_net(in_ch, out_ch, dim, n)

in_ch -> the number of channels in input out_ch -> the number of channels in output dim -> a dimensional parameter to modulate the number of parameters in the model. Default value is 64. Reducing or increasing the parameters would modulate the model accordingly. n -> number of paths. Default value is 2. Can be modulated to increase or decrease the complexity of the model.

network -> the returned model optimizer -> the optimizer associated with network is returned. Default value is Adam Optimizer with learning rate set to 1e^-4

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