Work with documents
Client:
Banks, financial institutions, retailers and government agencies. Details are under the NDA.
Banks, financial institutions, retailers and government agencies. Details are under the NDA.
Problem:
The challenge of document digitization is faced by many organizations. It is not uncommon for entire departments or workgroups to be involved in the process of digitizing document images. In addition to a significant investment of time, the human factor often affects when working with documents, people make mistakes or do not notice subtle differences in images, and manual control and data analysis requires additional resources.
The challenge of document digitization is faced by many organizations. It is not uncommon for entire departments or workgroups to be involved in the process of digitizing document images. In addition to a significant investment of time, the human factor often affects when working with documents, people make mistakes or do not notice subtle differences in images, and manual control and data analysis requires additional resources.
Solution:
Neural networks can be used to recognize the contents of checks and passports by performing optical recognition. It uses a machine learning algorithm to interpret and recognize characters in an image. By training a neural network on a large collection of images, it can be used for accurate recognition. These networks can identify personal data from the passport, such as name, date of birth, country of origin, and other details, as well as find any forgeries or inconsistencies. They can also be used to detect a passport photo, allowing it to be matched against other databases and identity documents.
In addition, neural networks will be useful for banks, financial institutions and retailers to automate the processing of check information such as payee, amounts and dates. This can reduce errors and save time in manual processes. The neural network will be trained using labeled data, such as images of receipts with relevant information.
Neural networks can be used to recognize the contents of checks and passports by performing optical recognition. It uses a machine learning algorithm to interpret and recognize characters in an image. By training a neural network on a large collection of images, it can be used for accurate recognition. These networks can identify personal data from the passport, such as name, date of birth, country of origin, and other details, as well as find any forgeries or inconsistencies. They can also be used to detect a passport photo, allowing it to be matched against other databases and identity documents.
In addition, neural networks will be useful for banks, financial institutions and retailers to automate the processing of check information such as payee, amounts and dates. This can reduce errors and save time in manual processes. The neural network will be trained using labeled data, such as images of receipts with relevant information.
