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Aesthetic classification of face images based on convolutional neural network model

  • Aimed at the problem that the accuracy of face image classification in complex environment is not high, a network model F-Net suitable for aesthetic classification of face images is proposed. Based on LeNet-5, the model uses convolutional layers to extract facial image features in complex backgrounds, optimized parameters in the network model, and changes the number of convolutional layers and fully connected layer feature elements in the model. The experimental results show that the F-Net network model proposed in this paper has a face image classifation accuracy of 73% in complex environment background, which is better than other classical convolutional neural network classification models.

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Author of HS ReutlingenRätsch, Matthias
Erschienen in:Journal of Xi'an Polytechnic University
Publisher:Xi'an Polytechnic University
Place of publication:Xi'an
Document Type:Journal article
Publication year:2019
Tag:LeNet-5; aesthetic classification; convolutional neural network; face recognition; image processing
Page Number:7
First Page:673
Last Page:678
DDC classes:600 Technik, Medizin, angewandte Wissenschaften
Open access?:Nein