计算机科学
信息图表
图表
任务(项目管理)
注释
情报检索
人工智能
数据挖掘
机器学习
自然语言处理
统计
数学
经济
管理
作者
Kenny Davila,Xu Fei,Saleem Ahmed,David A. Mendoza,Srirangaraj Setlur,Venu Govindaraju
标识
DOI:10.1109/icpr56361.2022.9956289
摘要
The outcomes of the third Challenge on HArvesting Raw Tables from Infographics (ICPR 2022 CHART-Infographics) are presented in this work. Recognizing charts is a difficult process which we divided into the following task: Chart Image Classification (Task 1), Text Detection and Recognition (Task 2), Text Role Classification (Task 3), Axis Analysis (Task 4), Legend Analysis (Task 5), Plot Element Detection and Classification (Task 6.a), Data Extraction (Task 6.b), and End-to-End Data Extraction (Task 7). We have provided a novel dataset for training reusing all available data from previous challenges, and we also provide a brand new testing dataset for the evaluation of submissions. Both datasets were constructed by manually annotating charts extracted from the Open Access section of the PubMed Central. A total of 9 teams registered out of which 5 submitted results for different tasks of the challenge. Many submissions are based on state-of-the-art methods from computer vision, but the final scores imply that more work will be required to solve the chart recognition problem. The data, annotation tools, and evaluation scripts have been publicly released for academic use.
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