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On May 7, the final and award-giving ceremony of 2019 Digital China Innovation Competition were held at Fuzhou Strait International Conference & Exhibition Center. Wang Qinmin, Vice Chairman of the 12th CPPCC and General Counselor of the Competition, and Li Dejin, Vice Governor of Fujian Province, attended the ceremony and presented the awards to the winning teams.Yang Xueshan, professor of Peking University and former Vice Minister of the Ministry of Industry and Information Technology, and Ni Guangnan and Li Peigen, both academicians of the CAS, delivered a keynote speech at the opening ceremony.This Competition has “Software-enabled Digital Economy and Innovation-driven Digital China” as its theme and designates six algorithm questions in the three major categories of big data, artificial intelligence and industrial Internet, i.e. “Cultural Inheritance​: Multi-scene Identification of Chinese Calligraphy”,“Intelligent Tallying: AI Counting of Reinforcing Bars”, “Big Data Medicine: AI Diagnosis of Liver Cancer Images”, “Consumer Group Portrait: Intelligent Credit Rating”, “Intelligent Remedy of Offshore Wind farm SCADA Data Loss” and“Concrete Pump Truck Concrete Piston Failure Prelim”. All these questions have originated from the practical application scenes of Huawei, China Mobile, Golden Software, CECDATA and other enterprises and reflect the current social and industrial development needs. At the final, the 18 shortlisted teams, which stood out among all 8,000-odd teams during the online tryout and the division competition, fully demonstrated their charms and enlisted works through team introduction, solution explanation and expert Q&A. The judges scored the teams strictly according to the evaluation rules and determined the 1st, 2nd and 3rd prize winners of the six questions after a whole day’s fierce competition. The winners of four individual awards, i.e. Best Commercial Potential Award, Best Algorithm Competence Award, Best Innovation Value Award and Best Field Performance Award, were also selected. Huawei Cloud BU (Enterprise Intelligence) provided Cultural Inheritance: Multi-scene Identification of Chinese Calligraphy competition. Senior artificial intelligence engineer Wang Jing introduced the background and hard points of the problem…

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A unified scheme of text localization and structured data extraction for joint OCR and data mining —— big data and artificial intelligence area

Abstract:

Both text detection and structured data extraction are imperative in an optical character recognition (OCR) processing pipeline. Text detection, especially for indistinct, diverse, multi-language text regions, is one of the most challenging tasks in computer vision and has attracted increasing attention recently. Moreover, although there are some studies in data mining related to structured data extraction, it has not received its deserved attention as one of important steps in OCR. The previous methods for structural data extraction, including layout template-based, rule-based, and natural language processing (NLP)-based methods, usually leads to either inaccurate results or complex modules. In this paper, we integrate text detection and structured data extraction into a unified deep learning-based Image Text Extraction (ITE) scheme. Our ITE is an end-to-end trainable model and able to handle multi-scale and multi-lingual text in a single process. Experiments on large-scale real-world passport and medical receipt datasets have demonstrated the superiority of the proposed method in terms of both effectiveness and efficiency.

Authors：Yibin Ye ; Shenggao Zhu ; Jing Wang ; Qi Du ; Yezhang Yang ; Dandan Tu ; Lanjun Wang ; Jiebo Luo（Cloud BU, Huawei Technologies）

https://ieeexplore.ieee.org/document/8622129/