Learning to represent 2D human face with mathematical model
Abstract How to represent a human face pattern? While it is presented in a continuous way in human visual system, computers often store and process it in a discrete manner with 2D arrays of pixels. The authors attempt to learn a continuous surface representation for face image with explicit function...
Päätekijät: | Liping Zhang, Weijun Li, Linjun Sun, Lina Yu, Xin Ning, Xiaoli Dong |
---|---|
Aineistotyyppi: | Artikkeli |
Kieli: | English |
Julkaistu: |
Wiley
2024-02-01
|
Sarja: | CAAI Transactions on Intelligence Technology |
Aiheet: | |
Linkit: | https://doi.org/10.1049/cit2.12284 |
Samankaltaisia teoksia
-
A Review of Face Recognition Technology
Tekijä: Lixiang Li, et al.
Julkaistu: (2020-01-01) -
Understanding of facial features in face perception: insights from deep convolutional neural networks
Tekijä: Qianqian Zhang, et al.
Julkaistu: (2024-04-01) -
MATHEMATICS LEARNING PROCESS AND RESULTS OF ELEMENTARY SCHOOL STUDENTS IN LIMITED FACE-TO-FACE LEARNING
Tekijä: Ariani Haffidah Lestari, et al.
Julkaistu: (2023-04-01) -
A Systematic Review of CNN Architectures, Databases, Performance Metrics, and Applications in Face Recognition
Tekijä: Andisani Nemavhola, et al.
Julkaistu: (2025-02-01) -
SeqFace: Learning discriminative features by using face sequences
Tekijä: Wei Hu, et al.
Julkaistu: (2021-09-01)