Feature learning via partial differential equation with applications to face recognition

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Cite
Fang, Cong, et al. “Feature Learning via Partial Differential Equation With Applications to Face Recognition”. Pattern Recognition, vol. 69, 2017, pp. 14-25, https://doi.org/10.1016/j.patcog.2017.03.034.
Fang, C., Zhao, Z., Zhou, P., & Lin, Z. (2017). Feature learning via partial differential equation with applications to face recognition. Pattern Recognition, 69, 14-25. https://doi.org/10.1016/j.patcog.2017.03.034
Fang C, Zhao Z, Zhou P, Lin Z. Feature learning via partial differential equation with applications to face recognition. Pattern Recognition. 2017;69:14-25.
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Citations
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A multi-rank two-dimensional CCA based on PDEs for multi-view feature extraction Expert Systems with Applications
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 2024
A new PDE learning model for image denoising Neural Computing and Applications
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Research on deep learning image processing technology of second-order partial differential equations Neural Computing and Applications
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A novel supervised correlation analysis based on partial differential equations for multi-feature extraction and fusion Multimedia Tools and Applications
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Citations Analysis
Category Category Repetition
Science: Mathematics: Instruments and machines: Electronic computers. Computer science8
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks6
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics6
Science: Science (General): Cybernetics: Information theory5
Technology: Engineering (General). Civil engineering (General)4
Science: Mathematics4
Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication3
Technology: Mechanical engineering and machinery3
Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software3
Science: Physics3
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware2
Technology: Electrical engineering. Electronics. Nuclear engineering1
Technology: Manufactures: Production management. Operations management1
Technology: Technology (General): Industrial engineering. Management engineering: Information technology1
Technology: Technology (General): Industrial engineering. Management engineering: Applied mathematics. Quantitative methods1
Technology: Photography1
The category Science: Mathematics: Instruments and machines: Electronic computers. Computer science 8 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled An effective few-shot learning approach via location-dependent partial differential equation and was published in 2019. The most recent citation comes from a 2024 study titled A multi-rank two-dimensional CCA based on PDEs for multi-view feature extraction. This article reached its peak citation in 2022, with 5 citations. It has been cited in 11 different journals, 27% of which are open access. Among related journals, the Advances in Mathematical Physics cited this research the most, with 3 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year