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Fig. 6 | BMC Biology

Fig. 6

From: WorMachine: machine learning-based phenotypic analysis tool for worms

Fig. 6

WormNet architecture. The network receives an input image of size 64 × 128 pixels and outputs a classification into worm or non-worm (noise) categories. The complete architecture is detailed in the figure and can also be viewed within the WorMachine’s open-source code. WormNet was trained on 11,820 mask images of worms and non-worms, randomly split into 85% training and 15% test set. It classified with 99.2% accuracy on the training set and 93.4% on the held-out test set

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