Image recognition based on deep learning in Haemonchus contortus motility assays
Authors/Creators
- 1. Charles University in Prague
Description
The repository contains the data associated with the paper `Image recognition based on deep learning in Haemonchus contortus motility assays`. The following folders form part of the repository:
- Annotation Data - annotated microscope images used for the training of the Mask R-CNN model. The data are divided into `train` and `val`
- Mask R-CNN - contains the trained weights for the Mask R-CNN model
- Motility Output - output of the 3 compared algorithms (Wiggle Index, WF-NTP and Mask R-CNN).
- Motility Videos - input videos used for the motility detection. The naming convetno is `XXXzYYY.avi`, where `XXX` denotes the motility group and `YYY` the sequence number for the video within a given group