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作者你好,我是一名非计算机专业的本科生,我已跑通你的代码,并把lenet换成了其他识别率更高的网络,。如果我想实现你未开源的部分,你有推荐的论文吗?我比较菜,一直没找到合适的论文。
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我这个项目采用的思路比较传统,现在有比较好的end-to-end的模型,其识别公式鲁棒性和精确度更好,你可以看看TAP(CNN+RNN+Attention)这个模型。如果你只是想学习,在我开源的基础上进行改进,参考两方面的文章,一个是对字符之间的关系进行分类。第二个是结构分析,这个可以参考编译原理的语法分析方法(算符优先法,或者递归下降法),或者二维文法。
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@Roujack 请问二维文法的英文术语叫什么?
不太清楚二维文法的术语,我的意思是那种考虑空间关系的文法。我觉的,现在基于规则的方法效果可能没有连接主义的方法好。目前跟CNN+RNN+Attention不同的做法,可能通过Graph convolution network去做,不清楚mathematical expression recognition有没有相关文献,在表格识别就有,参考Rethinking table recognition using graph neural networks
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作者你好,我是一名非计算机专业的本科生,我已跑通你的代码,并把lenet换成了其他识别率更高的网络,。如果我想实现你未开源的部分,你有推荐的论文吗?我比较菜,一直没找到合适的论文。
The text was updated successfully, but these errors were encountered: