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РецензированоEN2023

REAL-TIME OBJECT DETECTION AND CLASSIFICATION IN VIDEO IMAGES USING NEURAL NETWORKS

ТЕОРИЯ И ПРАКТИКА · Muminov Islom Bahodir o’g’li

Медицина, педагогика и технологии: теория и практика · 2 · 779-788 · 2023

Аннотация

This article explores the application of neural networks, specifically Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), in real-time object detection and classification within video streams. With the rapid evolution of computer vision technologies, neural networks have become the cornerstone of modern object detection systems. The paper delves into the architecture of these networks, their integration into real-time systems, and the accuracy and efficiency they provide for various applications such as autonomous vehicles, surveillance, and human-computer interaction. Key words. Real-time object detection, video classification, neural networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), computer vision, machine learning.

Доказательный фрагмент

«This article explores the application of neural networks, specifically Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), in real-time object detection and classification within video streams.»

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Демо-превью

This article explores the application of neural networks, specifically Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), in real-time object detection and classification within video streams. Полный текст публикации CiteX не хранит — доступ к первоисточнику открывается по DOI согласно лицензии издателя и выбранному плану.

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Узбекистан
Ключевые слова
Real-time object detection, video classification, neural networks, Recurrent Neural Networks (RNNs), computer vision, Convolutional Neural Networks (CNNs), machine learning
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