High Frequency Residual Learning for Multi-Scale Image Classification
arXiv: Computer Vision and Pattern Recognition, 2019.
We present a novel high frequency residual learning framework, which leads to a highly efficient multi-scale network (MSNet) architecture for mobile and embedded vision problems. The architecture utilizes two networks: a low resolution network to efficiently approximate low frequency components and a high resolution network to learn hig...More
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