System that allows you
to quickly check the logo
for plagiarism

Search for similar images

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Отрисовка логотипа для проверки
Поиск похожих изображений

About client

01/
INTELSONLINE is a large patent office. Deals with the preservation of intellectual property. Has been working since 1988.

INTELSONLINE has a service poiskznakov.ru

Who is it for?
experts in the field of intellectual property
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It allows you to check online if your trademark is a duplicate
creative offices
companies registering a trademark or trademark

Tasks the client came with:

02/
INTELSONLINE came with a ready request for a neural network:
We have finalized it and expanded the capabilities of the service
The client had a non-working, "raw" algorithm
improvement
support
01
02
This project grew out of EORA MAGE, an image search engine on any knowledge domain. Our technology is already widely used in the field of e - commerce.

Interesting fact

Development process

03/
Patent experts:
The process took
selected 100 trademarks and selected 50 similar ones for each.
Our development team:
trained the neural network on this dataset. Initially, there were no similarity criteria, the neural network had to select them based on examples.
4
months
Result:
a neural network trained on 5 thousand characters connects to the database of existing trademarks - there are 1.5 million of them. The system checks the user's logo for similarity to them.

System operation diagram

04/
User uploads a logo image:
The neural network compares it with trademarks registered in the CIS countries, the Baltic States, as well as the Database of the World Intellectual Property Organization
Our system produces a list of trademarks with a visually similar logo - potential plagiarism:
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The list is ranked - the most similar trademarks are shown first. This saves the experts' time.
Cписок товарных знаков с визуально сходным логотипом

Project team

05/
Computer Vision Engineer
MLOps engineer
Project manager
Data scientist
BackEnd developer
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Difficulties of the project

06/
In data science, there is always a risk that nothing will work out, simply because the right tools have not yet appeared. It usually takes a long time to find them.
But here everything worked out. We picked up a working algorithm, achieved 80% accuracy and corrected mistakes made by trainee developers in time.
Were poorly on time

What did we manage

07/
01
achieve 80 percent accuracy
show the most relevant images in the first hundred of results
save the customer the time of work of patent attorneys
02
03

Mass media wrote about us

08/
Article on the company's website
«How to find all similar images in 5 seconds»
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"... As a result, we stopped at the development from the Russian company EORA, which creates dialogue systems (chat bots) with high recognition accuracy, as well as solutions with OCR - what we need. Their product for image recognition and comparison is now called EORA MAGE. "

Our plans

09/
speed up the service
submit new pictures to the database so that the neural network can train on them
Contact us