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Detecting Erase Strokes from Online Handwritten Notes using Support Vector Classification

机译：使用支持向量分类检测来自网上手写笔记的擦写

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摘要

We have implemented a student note-sharing system, AirTransNote, that facilitates collaborative and interactive learning in conventional classrooms. With the AirTransNote system, a teacher can immediately share student notes with the class using a projection screen to enhance group learning. However, students tend to hesitate to share their notes, particularly when the notes contain embarrassing mistakes. Nevertheless, teachers want to focus on real mistakes students make while learning. We introduce an erase stroke detecting method for the student note-sharing system to reduce students' discomfort regarding sharing mistakes, as well as to assist the teacher in finding mistakes. We collected and manually labeled free-style handwritten student notes. Based on the labeled notes, we extracted features for the erase symbols and deleted strokes. We have tested support vector machine techniques for classifying erase symbols and deleted strokes from typical handwritten notes.
机译：我们已经实施了学生说明共享系统，航空公司，促进了传统教室中的协作和互动学习。通过AirTransnote系统，一名教师可以立即使用投影屏幕与类共享学生笔记，以增强组学习。然而，学生往往犹豫，分享他们的笔记，特别是当票据包含令人尴尬的错误时。尽管如此，教师希望专注于学习的真正错误。我们为学生说明分享系统介绍了一个擦除的行程检测方法，以减少学生对分享错误的不适，以及协助教师发现错误。我们收集和手动标记了自由风格的手写学生笔记。基于标记的注释，我们提取了删除符号和删除笔划的功能。我们已经测试了支持向量机技术，用于对典型的手写笔记进行分类擦除符号和已删除的笔画。

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