Privileged Learning Using Regularization in the Problem of Evaluating the Human Posture

被引：2
|
作者：
Kaprielova, M. S. [1 ]
Neichev, R. G. [2 ]
Tikhonov, A. D. [2 ]
机构：
[1] Russian Acad Sci, Fed Res Ctr Comp Sci & Control, Moscow 119333, Russia
[2] Moscow Inst Phys & Technol, Dolgoprudnyi 141701, Moscow Oblast, Russia
来源：
JOURNAL OF COMPUTER AND SYSTEMS SCIENCES INTERNATIONAL | 2023年 / 62卷 / 03期
关键词：
Compendex;
D O I：
10.1134/S1064230723030061
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The problem of evaluating a person's posture from video data is solved. Various key points of the human body are analyzed. We study the change in the accuracy of a fixed model when using different proportions in the regularization term of the loss function. It is shown that for a fixed number of training epochs, the accuracy of the model differs depending on the selected proportions. In addition, it is shown that the linear correlation between the trajectories of the key points that are part of the regularization term is not the main criterion for predicting the effectiveness of applying the regularization term of the loss function.
引用
收藏
页码：538 / 541
页数：4
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