Open AccessP_VggNet: A convolutional neural network (CNN) with pixel-based attention map
Author(s) -
Kunhua Liu,
Peisi Zhong,
Yi Zheng,
Kaige Yang,
Mei Liu
Publication year - 2018
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0208497
Subject(s) - computer science , convolutional neural network , artificial intelligence , pattern recognition (psychology)
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.