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Appl. Sci. 2018, 8(9), 1601; https://doi.org/10.3390/app8091601

Multiple Network Fusion with Low-Rank Representation for Image-Based Age Estimation

School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
Current address: Ligong Road #600, Houxi Town, Jimei District, Xiamen 361024, Fujian Province, China.
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Received: 9 August 2018 / Revised: 26 August 2018 / Accepted: 3 September 2018 / Published: 10 September 2018
(This article belongs to the Special Issue Advanced Intelligent Imaging Technology)
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Abstract

Image-based age estimation is a challenging task since there are ambiguities between the apparent age of face images and the actual ages of people. Therefore, data-driven methods are popular. To improve data utilization and estimation performance, we propose an image-based age estimation method. Theoretically speaking, the key idea of the proposed method is to integrate multi-modal features of face images. In order to achieve it, we propose a multi-modal learning framework, which is called Multiple Network Fusion with Low-Rank Representation (MNF-LRR). In this process, different deep neural network (DNN) structures, such as autoencoders, Convolutional Neural Networks (CNNs), Recursive Neural Networks (RNNs), and so on, can be used to extract semantic information of facial images. The outputs of these neural networks are then represented in a low-rank feature space. In this way, feature fusion is obtained in this space, and robust multi-modal image features can be computed. An experimental evaluation is conducted on two challenging face datasets for image-based age estimation extracted from the Internet Move Database (IMDB) and Wikipedia (WIKI). The results show the effectiveness of the proposed MNF-LRR. View Full-Text
Keywords: age estimation; multi-modal features; deep learning; low-rank representation age estimation; multi-modal features; deep learning; low-rank representation
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Hong, C.; Zeng, Z.; Wang, X.; Zhuang, W. Multiple Network Fusion with Low-Rank Representation for Image-Based Age Estimation. Appl. Sci. 2018, 8, 1601.

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