Improving the Generalisability of Deep CNNs by Combining Multi-stage Features for Surgical Tool Classification.

Dataset characteristics play an important role in training convolutional neural networks (CNNs) to evolve optimal features required to perform a specific task. Due to the high cost of recording and labelling surgical data, available datasets are relatively small in size and have been predominantly acquired at single sites. CNN-based approaches have been widely adapted to analyse surgical workflow using single-site datasets.