Super-low resolution face recognition using integrated Efficient Sub-Pixel Convolutional Neural Network (ESPCN) and Convolutional Neural Network (CNN)

Talab, Mohammed Ahmed and Suryanti, Awang and Najim, Saif Al-din M. (2019) Super-low resolution face recognition using integrated Efficient Sub-Pixel Convolutional Neural Network (ESPCN) and Convolutional Neural Network (CNN). In: IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS 2019) , 29 June 2019 , Shah Alam, Malaysia. pp. 1-5.. ISBN 978-1-7281-0784-4

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DOI/Official URL: https://doi.org/10.1109/I2CACIS.2019.8825083

Abstract

Several deep image-based models which depend on deep learning have shown great success in the recorded computational and reconstruction efficiencies, especially for single high-resolution images. In the past, the use of superresolution was commonly characterized by interference, and hence, the need for a model with higher performance. This study proposed a method for low to super-resolution face recognition, called efficient sub-pixel convolution neural network. This is a convolutional neural network which is usually employed at the time of image pre-processing to increase the chances of recognizing images with low resolution. The proposed Efficient Sub-Pixel Convolutional Neural Network is used for the conversion of low-resolution images into a high-resolution format for onward recognition. This conversion is based on the features extracted from the image. Using several evaluation tools, the proposed Efficient Sub-Pixel Convolutional Neural Network recorded a higher performance in terms of image resolution when compared to the performance of the benchmarked traditional methods. The evaluations were carried out on a Yale face database and ORL dataset faces. For Yale and ORL datasets, the obtained accuracy of the proposed method was 95.3% and 93.5%, respectively, which were higher than those of the other related methods.

Item Type:	Conference or Workshop Item (Lecture)
Uncontrolled Keywords:	Super-resolution (SR); Face recognition; Low resolution (LR); Deep learning
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Faculty/Division:	Faculty of Computer System And Software Engineering
Depositing User:	Pn. Hazlinda Abd Rahman
Date Deposited:	23 Dec 2019 04:34
Last Modified:	08 Jan 2024 04:50
URI:	http://umpir.ump.edu.my/id/eprint/26467
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