Appendix 1—figure 3. Schematics of the MoCoV2 algorithm and UNet-ResNet50 model architecture.

(a) Shows a single step in the MoCoV2 algorithm. A batch of images is copied; images in each copy of the batch are independently and randomly transformed and then shuffled into a random order (the first batch is called the query and the second is called the key). Query and key are encoded by two different models, the encoder and momentum encoder, respectively. The encoded key is appended to the queue. Dot products of every image in the query with every image in the queue measure similarity. The similarity between an image in the query and its match from the key is the signal that informs parameter updates. More details in He et al., 2019. (b) Detailed schematic of the UNet-ResNet50 architecture.