VIDEOTASVIRLARDAN OLINGAN MA’LUMOTLAR ASOSIDA SHAXS POZASINI TANIB OLISHNING NEYROTARMOQLI MODELI

I. K. Himmatov
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Abstract

Nowadays, there are several ways of recognizing and identifying a person, and these keep enhancing day by day. However, cases of falsification of these methods can also be observed. Modern video surveillance systems keep on developing, and satellite systems enable us to photograph everything that happens in a certain area and analyze effectively the data obtained using neural networks. Video images help to monitor motions of people, detect illegal entries into prohibited areas, as well as to identify remaining criminals by means of photos taken from cameras and control exit and/or entry of wanted criminals to foreign countries by acquiring other biometric data. This system serves to catch criminals at airports, railway stations, seaports; it automatically counts numbers of people in a line or in a crowd and analyzes the nature of their movements, which lessens the amount of subjective human intervention and reduces time required for data processing. Moreover, neural network-based pose estimation system is now being used widely in sports, and this can distinguish between athletes and change their behavior based on their personal characteristics.
videotasvirlardan olingan ma'lumotlar asosida shaxs pozasini tanib olishning neyrotarmoqli modeli
如今,有几种识别和识别一个人的方法,这些方法每天都在增加。然而,也可以观察到这些方法被证伪的情况。现代视频监控系统不断发展,卫星系统使我们能够拍摄一定区域内发生的一切,并利用神经网络对所获得的数据进行有效分析。视像有助监察人的活动、侦测非法进入禁区的人士,以及透过摄影机拍摄的照片,甄别残余的罪犯,以及透过取得其他生物特征资料,管制被通缉的罪犯出入境。该系统用于在机场、火车站、海港抓捕罪犯;它会自动计算队列或人群中的人数,并分析他们的运动性质,这减少了主观人为干预的数量,减少了数据处理所需的时间。此外,基于神经网络的姿态估计系统目前在体育运动中得到了广泛的应用,该系统可以根据运动员的个人特征来区分运动员并改变他们的行为。
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