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What is Yandex Vision?

Yandex Vision OCR excels at detecting and extracting text from images, including the addition of automatic punctuation to the results it generates. This sophisticated tool can effortlessly recognize and accommodate more than 50 languages. It proficiently extracts standard fields and processes text from a diverse array of templates and documents, such as passports, driver's licenses, vehicle registration certificates, and license plates. The technology is adept at managing both Russian and English languages, allowing it to handle combinations of handwritten and printed text without issue. Furthermore, it intelligently interprets table structures, presenting text in neatly organized row and column formats. Beyond its optical character recognition (OCR) and document identification capabilities, the system also features functionalities for recognizing license plate numbers. Yandex Vision OCR accepts file formats like JPEG, PNG, and PDF, supporting a maximum file size of 20 MB and accommodating documents of up to 300 pages. Impressively, the service can effectively scan images to identify passports from 20 different nations, in addition to various types of driver’s licenses, vehicle registration documents, and license plates, showcasing its adaptability for document processing tasks. Overall, its ability to streamline text recognition processes across a multitude of applications significantly enhances efficiency and accuracy. As technology continues to evolve, the potential uses for Yandex Vision OCR may expand even further, inviting new opportunities for integration in various fields.

What is Synap OCR?

Synap OCR is a cutting-edge optical character recognition system powered by AI that converts text from various image formats into editable documents. By harnessing the extensive knowledge of Synapsoft in digital document management and leveraging sophisticated deep learning methods, it achieves impressive accuracy in text recognition. To further improve its OCR capabilities, SynapSoft retains user-uploaded images for testing purposes, which plays a crucial role in enhancing the system's performance and user satisfaction. This retention not only bolsters the recognition rate but also contributes significantly to the overall user experience. The solution is distinguished by its high accuracy rate and swift processing capabilities. Ongoing improvements are made by continuously expanding the training dataset. Moreover, it utilizes an in-house developed rotation correction algorithm to ensure precise text recognition. The platform also gathers a wealth of OCR training data through its own document rendering technologies. Synap OCR successfully addresses recognition challenges posed by factors such as unusual fonts, image distortion, and background noise. In addition, it leverages specialized domain dictionaries to further refine accuracy, demonstrating a relentless pursuit of excellence in its performance. This dedication to delivering top-notch results solidifies Synap OCR's reputation as a leading choice for those in need of dependable OCR solutions, making it a standout option in the market.

Media

Media

Integrations Supported

Yandex Cloud

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

Windows
Linux

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Yandex

Date Founded

1997

Company Location

Russia

Company Website

cloud.yandex.com/en/services/vision

Company Facts

Organization Name

Synapsoft

Company Location

South Korea

Company Website

www.synapsoft.co.kr/ocr

Categories and Features

Computer Vision

Not specified

OCR

Not specified

Categories and Features

OCR

Not specified

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