Deep learning approaches to landmark detection in tsetse wing images
Fig 4
The network is composed entirely of convolutional layers.
It can be divided into downsampling and symmetric upsampling blocks. The output is of dimension 11 × 224 × 224, where each output segmentation map is a binary image with a disk centred at a particular landmark.