The Cloudwalk Pixer-Anchor text detection algorithm can identify and structurally output text information on test sets with multiple formats and interference such as complicated background, shadow, crease, seal, watermark, serial and dislocations. In ICDAR2015 and 2017 MLT, this algorithm refreshed the world record in detection accuracy and efficiency, winning the first place in many POC tests in the banking industry.
With automatic recognition training algorithm, automatic adaptation and reconstruction algorithm, automatic tagging and correction algorithm, text detection and format analysis algorithm as well as technologies such as semantic understanding and automatic integration, the Cloudwalk OCR automatic training platform automatically tags and trains pictures, and produces a text recognition model that can be used in the real environment without basic data, realizing “tagging while training”.
Background and challenges
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With the continuous increase in operational management costs, it is necessary to optimize personnel and store efficiency through digital means. -
Focusing on serving consumers, continuously changing operational strategies through multi-dimensional understanding of consumers, and continuously improving satisfaction. -
Reduce data blind spots, gain insight into every operational detail of the store, and create a digital and intelligent store.
