Abstract

The Internet not only provides help for people to understand the world and facilitate life, but also provides a convenient way for widespread dissemination of bad information. It follows that young people are often harassed by pornographic, violent and other bad images, which affects the development of young people's empathy. In this study, from the perspective of the combination of bad image screening and youth empathy ability, the effect of bad image on youth empathy ability is studied. In this article, a new empathy analysis model is constructed based on traditional empathy theory, combined with image recognition and data mining technology. First, the theoretical principles of bad image recognition technology and their application in the evaluation of empathy ability are expounded. Then, based on image recognition and fusion particle swarm optimization algorithm, the classification of bad images was studied. Finally, on the basis of image classification, a data envelopment model is used to grade the young people's empathy ability. The actual case analysis and performance test results illustrate the superiority of the implemented image classification and empathy evaluation method based on image recognition and data mining. This research has certain theoretical significance for the research of enriching empathy ability and interpersonal relationship. At the same time, it has certain practical significance for improving the youth's interpersonal trust, realizing the harmonious interpersonal relationship and the healthy development of body and mind.

Highlights

  • With the rapid development of information technology and Internet technology, network information has become a well-known convenient source of information and a leisure method [1]

  • This paper introduces the principle of particle swarm algorithm, and describes the basic framework of particle swarm algorithm training and poor image recognition algorithm based on particle swarm algorithm

  • With the help of mathematical methods and statistical data to determine the production frontier of relative effectiveness, each decision unit is projected onto the production frontier of DEA, and their relative effectiveness is evaluated by comparing the degree to which the decision unit deviates from the frontier of DEA [25,26]

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Summary

INTRODUCTION

With the rapid development of information technology and Internet technology, network information has become a well-known convenient source of information and a leisure method [1]. Forsyth used computer vision and image understanding technology to study the recognition of bad images, and judged whether the images contained pornographic content by detecting the geometric features of skin color segmentation and human posture [6]. Titchener mentioned the concept of "empathy" in English for the first time He believed that empathy is a process in which an individual actively and diligently enters another person's inner world [10]. Based on this, based on the theory of empathy ability, combined with image recognition and data mining technology, this paper builds a new empathy ability classification model. This method can provide scientific reference and basis for the research of modern empathy ability

SCREENING OF BAD INFORMATION BASED ON IMAGE
EVALUATION OF EMPATHY
BAD IMAGE CLASSIFICATION BASED ON PARTICLE
EVALUATION OF EMPATHY ABILITY BASED ON DATA
CLASSIFICATION OF BAD IMAGES BASED ON DATA
CONCLUSION
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