Detection of Anomalous Diffusion with Deep Residual Networks

Detection of Anomalous Diffusion with Deep Residual Networks

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Identification of the diffusion type of molecules in living cells is crucial to deduct their driving forces and hence to get insight into the characteristics of the cells.In this paper, deep residual networks have been used to classify the trajectories ah6789-001 of molecules.We started from the well known ResNet architecture, developed for image classification, and carried out a series of numerical experiments to adapt it to detection of diffusion modes.We managed to find a model that has state park 59fifty fitted a better accuracy than the initial network, but contains only a small fraction of its parameters.

The reduced size significantly shortened the training time of the model.Moreover, the resulting network has less tendency to overfitting and generalizes better to unseen data.