The primary learning strategies within SSL models in neuroimage-based medical applications. (IMAGE)
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In contrastive Learning, the graph-based approach generates augmented views of brain graphs to maximize view similarity through encoders and decoders, while the spatiotemporal-based approach focuses on leveraging temporal neural signals for similar contrastive objectives. Generative learning includes a mask-based method, which reconstructs randomly masked brain regions to minimize reconstruction loss, and a VAE-based method, where neural imaging data is encoded and reconstructed to learn global patterns. Lastly, Generative-contrastive learning combines generative modelling, such as GANs, with contrastive learning to capture intrinsic brain representations.
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Harbin Institute of Technology, Shenzhen
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