HANS: A Handwritten Answer Sheet Dataset for Noisy Hybrid Document Parsing· HANS: 手写答题纸数据集
Intelligent grading and automated scoring technologies constitute critical infrastructure for smart education. However, existing document parsing and handwriting recognition benchmarks are predominantly designed for well-structured printed documents or isolated mathematical expressions, lacking datasets that capture the complex characteristics inherent to student answer sheets, including multi-line derivation processes, heterogeneous mixtures of text and mathematical formulae, and noise artifacts such as strikethroughs. To address this gap, we introduce HANS, the first dataset explicitly constructed for real-world educational scenarios, encompassing mathematical expressions, natural language text, hand-drawn tables, and diverse noise patterns including corrections and deletions, accompanie
首个针对真实教育场景的手写答题纸数据集
- 核心方法
- 构建了包含数学表达式、自然语言文本、手绘表格和多种噪声模式(如修改和删除)的数据集HANS
- 适合谁读
- 研究人员、教育技术开发者
- 要解决的问题
- 现有数据集无法充分代表学生答题纸的复杂特性,如多行推导、文字与公式混合及各种噪声
- 关键实验
- 未提供
- 主要贡献
- 提供了首个专门针对学生手写答题纸解析的数据集,推动了智能评分和自动化评分技术的发展
- 意义与局限
- 填补了教育领域智能化技术的数据空白,但可能受限于特定场景的应用