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# Augmentation | ||
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[](https://github.com/achillet/Augmentation.jl/actions/workflows/CI.yml?query=branch%3Amain) | ||
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The Module Augmentation define some function to create a data augmentation. | ||
The objective is to add some channel model on the signals. This Modules can be used with synthetic data or with real. | ||
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The parameter N represents the augmentation factor. | ||
If N = 1 the function return a matrix wich has the same size as the input matrix and only applying channel model on data. | ||
If N = 2 the function return a matrix which is the double of the input matrix and apply two different channel. |
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# LatexConfusionMatrix | ||
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[](https://github.com/achillet/LatexConfusionMatrix.jl/actions/workflows/CI.yml?query=branch%3Amain) | ||
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The Module LatexConfusionMatrix allow to create Confusion Matrix for Latex based on csv file. |
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# Results | ||
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[](https://github.com/achillet/Results.jl/actions/workflows/CI.yml?query=branch%3Amain) | ||
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The Module Results allows to create graphics who show the F1 score evolution in function of time during the training or create CSV files with confusion Matrix obtained by infered Test Data on a network. |
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# RiFyFi_IdF | ||
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[](https://github.com/achillet/RiFyFi_IdF.jl/actions/workflows/CI.yml?query=branch%3Amain) | ||
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The Module RiFyFi_IdF defines function related to the classification/ Identification Framework particularly based on CNN |
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# RiFyFi_VDG | ||
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[](https://github.com/achillet/RiFyFi_VDG.jl/actions/workflows/CI.yml?query=branch%3Amain) | ||
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The Module RiFyFi_VDG defines function to create virtual database. |