基于发散学习的各种检测技术的实证研究

IF 0.2 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Bhagyashree Pramod Bendale, Swati Swati Dattatraya Shirke
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引用次数: 0

摘要

对妇女和儿童的暴力行为普遍存在,令人担忧,第一步是提高对这一问题的认识。某些形式的基于检测的技术通常不被社会和文化所允许。同时设计和实施有效的二级和辅助回避方法取决于特征和评估。鉴于发病率和死亡率较高,因此开发早期发现系统至关重要。因此,对妇女和儿童的暴力行为是一个严重影响人类健康的问题。因此,本次调查的重点是分析现有的方法,用于识别照片或电影中的暴力。本文回顾了50篇研究论文,并对其使用的技术、数据集、评估指标和发表年份进行了分析。该研究审查了未来可能的研究领域,审查了在文学作品中识别针对妇女和儿童的暴力行为的困难,供研究人员克服,以取得更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An empirical study of various detection based techniques with divergent learning’s
The prevalence of violence against women and children is concerning, and the initial step is to raise awareness of this issue. Certain forms of detection based techniques are not frequently regarded both socially and culturally permissible. Designing and implementing effective approaches in secondary and supplementary avoidance simultaneously depends on the characterization and assessment. Given the greater incidence of instances and mortalities resulting developing an early detection system is essential. Consequently, violence against women and children is a problem of human health of pandemic proportions. As a result, the focus of this survey is to analyze the existing methods used to identify violence in photos or films. Here, 50 research papers are reviewed and their techniques employed, dataset, evaluation metrics, and publication year are analyzed. The study reviews the potential future research areas by examining the difficulties in identifying violence against women and children in literary works for researchers to overcome in order to produce better results.
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来源期刊
Web Intelligence
Web Intelligence COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
0.90
自引率
0.00%
发文量
35
期刊介绍: Web Intelligence (WI) is an official journal of the Web Intelligence Consortium (WIC), an international organization dedicated to promoting collaborative scientific research and industrial development in the era of Web intelligence. WI seeks to collaborate with major societies and international conferences in the field. WI is a peer-reviewed journal, which publishes four issues a year, in both online and print form. WI aims to achieve a multi-disciplinary balance between research advances in theories and methods usually associated with Collective Intelligence, Data Science, Human-Centric Computing, Knowledge Management, and Network Science. It is committed to publishing research that both deepen the understanding of computational, logical, cognitive, physical, and social foundations of the future Web, and enable the development and application of technologies based on Web intelligence. The journal features high-quality, original research papers (including state-of-the-art reviews), brief papers, and letters in all theoretical and technology areas that make up the field of WI. The papers should clearly focus on some of the following areas of interest: a. Collective Intelligence[...] b. Data Science[...] c. Human-Centric Computing[...] d. Knowledge Management[...] e. Network Science[...]
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