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Automatic Traffic Sign Detection System With Voice Assistant

机译:带语音助手的自动交通标志检测系统

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摘要

In the arena of artificial intelligence, the world is revolutionizing with many technological applications being incorporated with Artificial Intelligence due to improved efficiency and performance. AI has penetrated drastically, delving deep into locker room decisions in many fields like agriculture, healthcare, military, manufacturing, robotics, transportation and so on. AI does a lot more than improving our lives, in most cases, it saves our lives too. Autonomous vehicles, the so-called self-driving cars, are one of the greatest applications of AI and are very instrumental in making the machine work autonomously by observing and interpreting the real-life scenario of the environment. This paper deals with the deployment of an Automatic Traffic sign detection System with voice assistant, which is one of the applications of autonomous vehicles, which can tone down the driver from puzzling traffic conditions significantly increasing driving safety and comfort. This will require an appropriate database and algorithm for improved accuracy in performance. This paper, therefore, compares the features, accuracy, and efficiency of various deep learning algorithms and comes up with a varied model thus saving computational resources.
机译:在人工智能领域,世界正在发生革命性的变化,由于效率和性能的提高,许多技术应用程序被与人工智能相结合。AI 已经彻底渗透,深入到农业、医疗保健、军事、制造、机器人、运输等许多领域的更衣室决策中。人工智能的作用不仅仅是改善我们的生活,在大多数情况下,它还可以挽救我们的生命。自动驾驶汽车,即所谓的自动驾驶汽车,是人工智能最伟大的应用之一,通过观察和解释环境的真实场景,在使机器自主工作方面发挥着重要作用。本文讨论了带有语音助手的自动交通标志检测系统的部署,这是自动驾驶汽车的应用之一,它可以减轻驾驶员对令人困惑的交通状况的影响,显着提高驾驶安全性和舒适性。这将需要适当的数据库和算法来提高性能的准确性。因此,本文比较了各种深度学习算法的特性、准确性和效率,并提出了一种不同的模型,从而节省了计算资源。

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