SimCLR architecture: the input image × undergoes random transformation twice, generating two views. These views are then processed through the encoder f (·) to extract corresponding representations. Subsequently, an MLP g(·) is employed to project these representations into a lower dimensional space. The objective of the learning task is to maximise the similarity between these projections.