P_VggNet: A convolutional neural network (CNN) with pixel-based attention map.

Journal: PloS one
Published Date: Dec 12, 2018

Abstract

Attention maps have been fused in the VggNet structure (EAC-Net) [1] and have shown significant improvement compared to that of the VggNet structure. However, in [1], E-Net was designed based on the facial action unit (AU) center and for facial AU detection only. Thus, for the use of attention maps in every image type, this paper proposed a new convolutional neural network (CNN) structure, P_VggNet, comprising the following parts: P_Net and VggNet with 16 layers (VggNet-16). The generation approach of P_Net was designed, and the P_VggNet structure was proposed. To prove the efficiency of P_VggNet, we designed two experiments, which indicated that P_VggNet could more efficiently extract image features than VggNet-16.

Authors

  • Kunhua Liu
    Advanced Manufacturing Technology Center, Shandong University of Science and Technology, Qingdao, Shandong province, China.
  • Peisi Zhong
    Advanced Manufacturing Technology Center, Shandong University of Science and Technology, Qingdao, Shandong province, China.
  • Yi Zheng
    Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, 300211 Tianjin, China.
  • Kaige Yang
    Advanced Manufacturing Technology Center, Shandong University of Science and Technology, Qingdao, Shandong province, China.
  • Mei Liu
    Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, Kansas City, Missouri, USA.

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