混合光栅和矢量PDF的图形和图形标题提取：具有OCR特征的天文文献的数字化
Figure and Figure Caption Extraction for Mixed Raster and Vector PDFs: Digitization of Astronomical Literature with OCR Features
摘要：
20世纪90年代末“数字化时代”之前发表的科学文章包含“被困”在扫描页面中的数字。虽然在提取数字及其说明方面取得了进展，但目前还没有可靠的方法。我们提出了一种基于YOLO的方法，用于扫描页面，后光学字符识别（OCR），它使用灰度和OCR功能。当应用于天体物理学数据系统（ADS）的天体物理学文献时，我们发现F1分数为90.9%（92.2%）的图形（图形标题）与交叉联合（IOU）截止值为0.9，这是一个显着的改进，比其他国家的最先进的方法。
英文摘要：
Scientific articles published prior to the "age of digitization" in the late 1990s contain figures which are "trapped" within their scanned pages. While progress to extract figures and their captions has been made, there is currently no robust method for this process. We present a YOLO-based method for use on scanned pages, post-Optical Character Recognition (OCR), which uses both grayscale and OCR-features. When applied to the astrophysics literature holdings of the Astrophysics Data System (ADS), we find F1 scores of 90.9% (92.2%) for figures (figure captions) with the intersection-over-union (IOU) cut-off of 0.9 which is a significant improvement over other state-of-the-art methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
