丁克·亨特

Shubham Gulia, Anshika Agrawal, Harsh Jain, Dr. Ankita Gupta
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引用次数: 0

摘要

近年来,随着科技占据了大部分的生活过程,小学教育在“边做边学”的过程中仍然缺乏使用技术的互动过程。大多数教育技术提供视觉学习,没有或几乎没有孩子的输入。Tinker Hunt可以成为解决相同问题的交互式学习应用程序之一。孩子们输入一个粗略的草图,可以在互联网上以图片、详细信息等形式产生结果。Tinker Hunt是使用谷歌的QuickDraw数据集创建的,该数据集使用了数百种草图模式,用于多个类别的图标级涂鸦,这些图案是从CNN训练模型识别的数百个人中收集的。此外,该应用程序在素描识别和分类方面的准确性也很高。关键词:机器学习;建立数据集;互动学习;卷积神经网络;人工神经网络
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tinker Hunt
With tech taking over most of the life process in recent times, primary education still lacks interactive processes using technology in the process of “Learning by Doing”. Most of the Ed. techs offer visual learning with no or near-to-zero input by children. Tinker Hunt can be a possible and one of its kind of interactive learning application used to tackle the same. A rough sketching input by children can yield results over the internet in the form of pictures, detailed information, etc. Tinker Hunt is created using Google’s QuickDraw Dataset, using hundreds of sketch patterns for multiple categories of icon-level doodles, collected from hundreds of individuals that are recognized by CNN trained model. Also, the app is tested for high accuracy in sketch recognition and categorization. Key Word: Machine Learning; QuickDraw Dataset; Interactive Learning; Convolutional Neural Network; Artificial Neural Network
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