A Trainable Multiplication Layer for Auto-correlation and Co-occurrence Extraction

@inproceedings{Hayashi2018ATM,
  title={A Trainable Multiplication Layer for Auto-correlation and Co-occurrence Extraction},
  author={Hideaki Hayashi and Seiichi Uchida},
  booktitle={ACCV},
  year={2018}
}
In this paper, we propose a trainable multiplication layer (TML) for a neural network that can be used to calculate the multiplication between the input features. Taking an image as an input, the TML raises each pixel value to the power of a weight and then multiplies them, thereby extracting the higher-order local auto-correlation from the input image. The TML can also be used to extract co-occurrence from the feature map of a convolutional network. The training of the TML is formulated based… Expand
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