Efficacy of deep convolutional neural networks in classification of AAVs from nanopore experimental data obtained at different applied potential difference: (a) −75 mV, (b) −100 mV, (c) −125 mV, (d) −150 mV and (e) −175 mV for 1 sec time frame images. For a particular class, 70% of the data were randomly selected from all images of that class for training the network, while the rest of the images of that class were used for validation.