Axborot texnologiyalari, tarmoqlar va telekommunikatsiyalar

Conclusion 
The use of artificial intelligence will also speed up the process of website 
development by programmers and increase site performance, as the translation will 
be reproduced on Yandex servers. It will also help to improve the activity on the 
site, as different people with different languages of communication will feel on the 
site as on the sites of their content. 
Used sources: 
1.
A Global Perspective on Bilingualism and Bilingual Education (1999), G. 
Richard Tucker, Carnegie Mellon University" (PDF). cal.org. Retrieved 8 May 
2018. 
2.
Hopfield, J. J. (1982). "Neural networks and physical systems with emergent 
collective computational abilities". Proc. Natl. Acad. Sci. U.S.A. 79 (8): 2554– 
2558. 
IVA SOFTWARE AS A PUBLIC SAFETY SYSTEM 
Khujaev Otabek, Rustamov Oybek, Allambayeva Yorqinoy 
Urgench branch of the Tashkent University of Information Technologies named 
after Muhammad Al-Khwarizmi, [e-mail], 
[e-mail]
 
 
Annotation: Day after day in the world, especially in countries where the economy 
is developed, where the population is larger than in other countries, more and 
more people are being lost for no reason. It is no exception that countries are 
beginning to struggle with this very problem, finding different ways to solve this 
problem. Uzbekistan also faced this problem. In addition, most of the wanted 
people are not only children aged 12 to 18, but also people over the age of 18. It is 
also possible that the wanted people may be criminals. It is also closely related to 
the safety of the population. 
Keywords: 
Artificial intelligence, computer vision, iva, computer vision, mlnet. 
Today, video surveillance is used everywhere. Detection systems are 
installed both on small objects and on large ones, which include dozens or even 
hundreds of video cameras. Large enterprises and various services, such as, for 
example, ATC, hire a large staff of video surveillance operators due to the huge 
flow of video information coming from cameras every second. 
But often people just can’t cope, missing important points related to security. 
You can add to this the human factor, when people cannot concentrate on some 
objects for a long time. Important and necessary data often pass by their attention. 
And here artificial intelligence can come to the rescue. Various companies offer 
their own solutions today, designed to make searching through the video archive 
simple and convenient. New technologies help operators to quickly find a specific 
person or vehicle. When the operator has a description of a person, the technology 
allows you to select his characteristics, such as gender or color of clothing. In the 
case of an emergency search for a missing person or suspect, this technology will 

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International scientific conference "INFORMATION TECHNOLOGIES, NETWORKS AND 
TELECOMMUNICATIONS" ITN&T-2022 Urgench, 2022y April 29-30 
375 
be especially useful, since it can use a description to search for a person within a 
few seconds. An example of detecting a person in a video is shown in picture 1. 
Picture 1. Face detection in a photo. 
To date, there are several face recognition algorithms. One of the well- 
managed algorithms is the Viola Jones algorithm, which is described in detail 
below. The Viola–Jones method is an algorithm that allows you to detect objects in 
images in real time. It was proposed by Paul Viola and Michael Jones in 2001. 
Although the algorithm can recognize objects in images, the main task when 
creating it was to detect faces.[1] 
IVA software uses artificial intelligence technologies to detect persons who 
are actively wanted. This system uses mainly computer vision and to obtain data, 
the system works with cameras on the streets, in cafes and other establishments. 
The IVA system is developed using technologies developed by Microsoft. It 
is developed using a machine learning library ML.NET developed by MSCorp. 
ML.NET brings model-based Machine Learning analytic and prediction 
capabilities to existing .NET developers. The framework is built upon .NET Core 
and .NET Standard inheriting the ability to run cross-platform on Linux, Windows 
and macOS. Although the ML.NET framework is new, its origins began in 2002 as 
a Microsoft Research project named TMSN for use internally within Microsoft 
products. It was later renamed to TLC around 2011. ML.NET was derived from 
the TLC library and has largely surpassed its parent says Dr. James McCaffrey, 
Microsoft Research.[2] 
Also, for the system to work, there is no need to change the already installed 
surveillance equipment, since the system processes the full picture and video 
surveillance devices serve only to take a picture for a certain period.