Document analysis tasks for which representative labeled training samples are available have been largely solved. The next frontier is coping with hitherto unseen formats, unusual typefaces, idiosyncratic handwriting and imperfect image acquisition. Adaptive and style-constrained classification methods can overcome some expected variability, but human intervention will remain necessary in many tasks. Interactive pattern recognition includes data exploration and active learning as well as access to stored documents. The principle of “green interaction” is to make use of every intervention to reduce the likelihood that the automated system will make the same mistake again and again. Some of these techniques may pop up in forthcoming personal camera-based memex-like applications that will have a far broader range of input documents and scene text than the current, successful but highly specialized, systems for patents, postal addresses, bank checks and books.

中文翻译：

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随着使用而改进的文档分析系统

可以使用具有代表性的标记培训样本的文档分析任务已得到很大解决。下一个领域是应对迄今为止看不见的格式，不寻常的字体，特有的笔迹和不完美的图像采集。自适应和受样式约束的分类方法可以克服某些预期的可变性，但是在许多任务中仍然需要人工干预。交互式模式识别包括数据探索和主动学习以及对存储文档的访问。“绿色互动”的原理是利用每种干预措施来减少自动化系统一次又一次犯同样错误的可能性。