Color image classification via quaternion principal component analysis network

@article{Zeng2016ColorIC,
  title={Color image classification via quaternion principal component analysis network},
  author={Rui Zeng and Jiasong Wu and Zhuhong Shao and Y. Chen and Beijing Chen and L. Senhadji and H. Shu},
  journal={ArXiv},
  year={2016},
  volume={abs/1503.01657}
}
The principal component analysis network (PCANet), which is one of the recently proposed deep learning architectures, achieves the state-of-the-art classification accuracy in various datasets and reveals a simple baseline for deep learning networks. [...] Key Method Compared to PCANet, the proposed QPCANet takes into account the spatial distribution information of RGB channels in color images and ensures larger amount of intra-class invariance by using quaternion domain representation for color images…Expand
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