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http://dx.doi.org/10.22156/CS4SMB.2021.11.07.001

Landmark Selection Using CNN-Based Heat Map for Facial Age Prediction  

Hong, Seok-Mi (Department of Liberal Arts, Sangji University)
Yoo, Hyun (Contents Convergence Software Research Institute, Kyonggi University)
Publication Information
Journal of Convergence for Information Technology / v.11, no.7, 2021 , pp. 1-6 More about this Journal
Abstract
The purpose of this study is to improve the performance of the artificial neural network system for facial image analysis through the image landmark selection technique. For landmark selection, a CNN-based multi-layer ResNet model for classification of facial image age is required. From the configured ResNet model, a heat map that detects the change of the output node according to the change of the input node is extracted. By combining a plurality of extracted heat maps, facial landmarks related to age classification prediction are created. The importance of each pixel location can be analyzed through facial landmarks. In addition, by removing the pixels with low weights, a significant amount of input data can be reduced.
Keywords
Convolutional Neural Network; Image Analysis; Artificial Neural Network; Image Classification; Face Recognition; Big Data;
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