基于深度学习预测 Wartegg-ZeichenTest 绘画图像中的青少年暴力行为

IF 3.2 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Connection Science Pub Date : 2023-12-26 DOI:10.1080/09540091.2023.2286186

Kyung-yeul Kim, Young-bo Yang, Mi-ra Kim, Ji Su Park, Jihie Kim

引用次数: 0

摘要

这篇论文探讨的是青春期身心压力变化导致的消极行为问题。特别是，它是一项研究，旨在解决暴露在压力下的学生的保健问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Predicting adolescent violence in Wartegg-ZeichenTest drawing images based on deep learning

This thesis deals with the problem of negative behaviour due to changes in mental and physical stress in adolescence. In particular, it is a study to solve the health care problem of students expos...

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来源期刊

Connection Science 工程技术-计算机：理论方法

CiteScore

6.50

自引率

39.60%

发文量

审稿时长

3 months

期刊介绍： Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing. A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.