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We demonstrate that automatic differentiation, which has become commonly available in machine learning frameworks, is an efficient way to explore ideas that lead to algorithmic improvement in multi-scale affine image registration and affine super-res
Externí odkaz:
http://arxiv.org/abs/2411.02806
