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Found 6 papers, 2 papers with code
From multiscale biophysics to digital twins of tissues and organs: future opportunities for in silico pharmacology
With many advancements in in silico biology in recent years, the paramount challenge is to translate the accumulated knowledge into exciting industry partnerships and clinical applications.
Feature transforms for image data augmentation
These novel methods are based on the Fourier Transform (FT), the Radon Transform (RT) and the Discrete Cosine Transform (DCT).
Comparison of different convolutional neural network activation functions and methods for building ensembles
Because activation functions inject different nonlinearities between layers that affect performance, varying them is one method for building robust ensembles of CNNs.
An Ensemble of Convolutional Neural Networks for Audio Classification
The best performing ensembles combining data augmentation techniques with different signal representations are compared and shown to outperform the best methods reported in the literature on these datasets.
Data augmentation approaches for improving animal audio classification
To the best of our knowledge this is the largest study on data augmentation for CNNs in animal audio classification audio datasets using the same set of classifiers and parameters.
Audiogmenter: a MATLAB Toolbox for Audio Data Augmentation
Audio data augmentation is a key step in training deep neural networks for solving audio classification tasks.
