FuseNet is a type of neural network architecture designed primarily for applications in image processing, particularly in tasks like image segmentation and classification. It combines features from different levels of a neural network to create a more robust representation of the input data. The architecture of FuseNet typically involves the integration of multi-scale features from various layers of a deep learning model.
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