Sichuan Vocational College of Cultural Industries, Chengdu 610000l, Sichuan, China.
Comput Intell Neurosci. 2022 Jun 6;2022:2373842. doi: 10.1155/2022/2373842. eCollection 2022.
Technological development has resulted in the utilisation of advanced technology search using deep learning technology in all industries. Artificial intelligence is set to be filled with machines that can perform tasks that need human intelligence. These machines are controlled by computer systems. In this study, people are going to analyse the traditional cultural acceptance based on deep learning. Deep learning technology is a subfield of machine learning that makes use of algorithms that are inspired by the human brain. Artificial neural network is one such network used in deep learning. Traditional cultural acceptance is an integration of traditional cultures and cultural acceptance. The traditional cultures are said to be the tribes that are never exposed to the technological radar. These communities live traditionally in remote areas where there is no access to the latest technologies. The traditional cultures were found in the upper Amazon regions. Because they have not been exposed to the modern world, they have retained their ancient traditional and cultural value. Cultural acceptance can be said in simple words: accepting people as they are, without shaming their culture, traditional habits, attire, and body. In this proposed system, deep learning techniques were used to analyse the traditional cultural acceptance. The results proved that the proposed model called Faster R-CNN performs well than the existing algorithms.
技术发展导致在各个行业都利用深度学习技术进行高级技术搜索。人工智能将充满能够执行需要人类智能的任务的机器。这些机器由计算机系统控制。在这项研究中,人们将基于深度学习分析传统文化的接受度。深度学习技术是机器学习的一个子领域,它利用受人类大脑启发的算法。人工神经网络是深度学习中使用的一种网络。传统文化的接受度是传统文化和文化接受度的融合。传统文化是指从未接触过技术雷达的部落。这些社区传统上生活在偏远地区,无法获得最新技术。传统文化在上亚马逊地区被发现。因为他们没有接触过现代世界,所以他们保留了古老的传统和文化价值。文化接受度可以简单地说:接受人们的本来面目,不羞辱他们的文化、传统习惯、着装和身体。在这个提出的系统中,使用深度学习技术来分析传统文化的接受度。结果证明,称为 Faster R-CNN 的提议模型比现有算法表现更好。