Automatic Language Detection
Zia can operate in an automatic mode and run its algorithms to detect and identify the language of the text in an input file. However, to speed up the text recognition process, the user can specify the language of the text, if they know it, while submitting it for OCR processing. This enables Zia to restrict its processing and analysis to a limited dataset, leading to quicker and more accurate results.
Zia OCR processes files and generates the results in a fast and effective manner. Catalyst ensures a high throughput of data transmission and a minimal latency in serving requests. The quick response time enhances your application’s performance, and provides a satisfying experience for the end user.
Highly Accurate and Reliable Results
Zia is an AI-driven assistant that undergoes repeated systematic training to generate results with higher accuracy and a lower error margin. The AI is trained using various machine learning techniques to perform complex computations and analysis. The training model is highly vigorous, which means it studies and analyzes large volumes of data, and this ensures that the results generated are precise, accurate, and reliable.
You can easily implement OCR in your application without having to worry about the underlying logic or the backend set-up. You can implement the ready-made code templates provided for the Java and Node.js platforms in any of your Catalyst applications that requires the use of OCR.
Testing in the Console
The testing feature in the console enables you to verify the efficiency of Zia OCR. You can upload sample images and documents with text, and view the results. This allows you to get an idea about the format and accuracy of the response that will be generated when you implement it in your application.
Last Updated 2023-05-19 12:11:43 +0530 +0530
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