The Method for Searching Emotional Content in Images Based on Low-Level Parameters with Using Neural Networks

被引：2

作者：

Vladimir, Rozaliev ^{[1
]}

Roman, Guschin ^{[1
]}

Yulia, Orlova ^{[1
]}

Alla, Zaboleeva-Zotova ^{[1
]}

Vladislav, Berdnik ^{[1
]}

机构：

[1] Volgograd State Tech Univ, 28 Lenin Ave, Volgograd, Russia

来源：

BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES 2018 | 2019年 / 848卷

关键词：

Human emotions; Image identification; Neural networks; Adaboost algorithm; Information system; INFORMATION;

D O I：

10.1007/978-3-319-99316-4_34

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper proposes a method to improve the modeling of subjectivity and human understanding based on the annotation of emotional semantics of images using the theory of fuzzy sets. Adaptive acceleration and reverse propagation of the neural network (BP). The annotation method was tested by analyzing images from the solar image database. In addition, the accuracy of the search is based on 85% of our method. This study is the basis for a more accurate semantic analysis and verification.

引用

页码：260 / 265

页数：6

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