A DDoS Attack Traffic Detection System Based on Deep Learning

Chen, Gong; Zhao, Yujuan; Shuai, Lisha; Luo, Jintang; Yang, Xiaolong

doi:10.1109/iccc54389.2021.9674582

Cited by 2 publications

(1 citation statement)

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“…Therefore, this paper mainly studies the UAV intelligent recognition and tracking method with deep learning as the core, in order to provide an effective basis for the research of intelligent UAV technology in the new era. [4][5][6]…”

Section: Introducionmentioning

confidence: 99%

Uav intelligent recognition and tracking method based on deep learning

Zhi,

Zhou,

Zhang

2023

AETR

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In the era of artificial intelligence, the traditional industry has undergone great changes under the guidance of modern technology theory. Enterprises or institutions in various fields have begun to develop and innovate UAV equipment with the application value of The Times with the help of technologies such as deep learning or machine vision to meet the increasing business processing needs. Since the unmanned aerial vehicle will transmit the captured images to the ground, and the encoding and decoding during transmission will affect the real-time performance of the overall system, scientific researchers have proposed an intelligent recognition and tracking method for unmanned aerial vehicles, in order to improve the work efficiency and quality of the system equipment. On the basis of understanding the current research status of UAV and target recognition technology, this paper mainly studies the UAV target recognition algorithm with deep learning as the core according to the intelligent UAV platform design scheme. The final result shows that the deep learning recognition algorithm can further improve the efficiency of UAV intelligent recognition and tracking.

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Section: Introducionmentioning

confidence: 99%