Smooth principal component analysis network image recognition algorithm with fusion graph embedding

doi:10.11887/j.cn.202203003

Home > Archive>Volume 44, Issue 3, 2022 >16-22. DOI:10.11887/j.cn.202203003

Smooth principal component analysis network image recognition algorithm with fusion graph embedding
DOI:
                        10.11887/j.cn.202203003
                    
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                        CHEN Feiyue1CHEN Feiyue
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
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ZHU Yulian2ZHU Yulian
Fundamental Experiment Teaching Department, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
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TIAN Jialue1TIAN Jialue
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
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JIANG Ke1JIANG Ke
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
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Affiliation:(1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;2. Fundamental Experiment Teaching Department, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)
Clc Number:TP391
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Abstract:

PCANet (principal component analysis network) is a simple deep learning algorithm with excellent performance in the field of image recognition. Integrating the idea of graph embedding into PCANet, a new image recognition algorithm Smooth-PCANet was proposed. In order to verify the effectiveness of the Smooth-PCANet algorithm, adequate experiments were performed on different data sets such as face, handwritten characters, and images. Compared with several image recognition algorithms based on deep learning, the experiments demonstrated that the Smooth-PCANet achieves higher recognition performance than the PCANet and avoids overfitting more effectively, with a significant advantage in small samples training.

Key words:image recognition; principal component analysis network; graph embedding; deep learning; small training set

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CHEN Feiyue, ZHU Yulian, TIAN Jialue, JIANG Ke. Smooth principal component analysis network image recognition algorithm with fusion graph embedding[J]. Journal of National University of Defense Technology,2022,44(3):16-22.

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Received:June 20,2021
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Online: June 02,2022
Published: June 28,2020

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