Abstract: Highlights•A region-wise CL is proposed to learn regional features from easy to hard.•An uncertainty-based regularization method is proposed to separate easy and hard regional features.•A dynamic fusion method is proposed to dynamically modulates the fusion weights of easy and hard regional features.•Extensive experimental results verify the superior performance of the proposed EH-Former.
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