DEVELOPMENT OF THE ALGORITHM OF THE OPTIMAL VARIANT OF HUMAN FACE DETECTION

Authors

  • Axadjon Tojimirzo ugli Naimov Master, TATU Department of Artificial Intelligence, Chief specialist of technology transfer, incubation and acceleration department.
  • Sherzod Xasanboy ugli Mavlonov Master, TATU Department of Artificial Intelligence, Leading expert of technology transfer, incubation and acceleration department.

Keywords:

human face detection, algorithm, optimal variant, computer vision, facial recognition, deep learning, convolutional neural networks (CNNs), ensemble learning, transfer learning, bias mitigation, privacy preservation.

Abstract

This article discusses the development of the algorithm of the optimal variant of human face detection. The goal of human face detection is to locate and identify human faces in digital images or videos, which has a wide range of applications in various fields such as security systems, facial recognition, and human-computer interaction.

References

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B. Wang, J. Li, Y. Wang, X. Liu and J. Lu, "EfficientNet-Face: A Scalable and Efficient Face Detection Network," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020

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Z. Liu, J. Guo, P. Li, Z. Li, Z. Li, and J. Yu, "Real-Time and Accurate Face Detection with Scale-Aware Refinement Network," IEEE Transactions on Image Processing, vol. 30, pp. 1343-1355, 2021

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Published

2023-01-26

How to Cite

Naimov , A. T. ugli, & Mavlonov, S. X. ugli. (2023). DEVELOPMENT OF THE ALGORITHM OF THE OPTIMAL VARIANT OF HUMAN FACE DETECTION. INTERNATIONAL CONFERENCES, 1(2), 713–716. Retrieved from http://erus.uz/index.php/cf/article/view/1626

Issue

Vol. 1 No. 2 (2023): INTERNATIONAL CONFERENCE ON TEACHING, EDUCATION AND NEW LEARNING TECHNOLOGIES 2023/2

Section

Articles