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Information Journal Paper

Title

Aggressive Flying Objects Detection System Using Image Sensor

Pages

  65-77

Abstract

 Advances in the technology of UAVs and MAVs have led to an expanse use of these drones which has brought both securing the information and safekeeping of particular areas such as stadiums, facilities, military and law enforcement agencies, that are being considered and managed more than before. Accordingly, defense mechanisms should be sized congenially to the exact type of thread dealing with these threats. The proposed system in this study is the uses only a high-resolution camera that identifies specified targets based on a given database. In recent studies, several methods such as using particle filters, Neural Networks systems, have been presented. They are reviewed in this work and then, using a combination of the mentioned techniques with a novel laboratory benchmark detector and tracker of the drone is designed and implemented. The main focus of the project is the use of convolutional Neural Networks, which should maximize the frame rate of the received data from the camera. This project is implemented using three different methods including Darknet Framework, YOLO, and Fast RCNN network. In all cases, framerates are processed. The expected average accuracy in this project is more than 90%. The presented system has been tested by computer but it has the capability of performing on FPGA environment using HLS tools.

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    APA: Copy

    Zeynali, Seyyed Mohammad Javad, NAJAFI AGHDAM, ESMAEIL, & Farrokhzadeh, Mahdi. (2021). Aggressive Flying Objects Detection System Using Image Sensor. INFORMATION AND COMMUNICATION TECHNOLOGY IN POLICING, 2(5 ), 65-77. SID. https://sid.ir/paper/957435/en

    Vancouver: Copy

    Zeynali Seyyed Mohammad Javad, NAJAFI AGHDAM ESMAEIL, Farrokhzadeh Mahdi. Aggressive Flying Objects Detection System Using Image Sensor. INFORMATION AND COMMUNICATION TECHNOLOGY IN POLICING[Internet]. 2021;2(5 ):65-77. Available from: https://sid.ir/paper/957435/en

    IEEE: Copy

    Seyyed Mohammad Javad Zeynali, ESMAEIL NAJAFI AGHDAM, and Mahdi Farrokhzadeh, “Aggressive Flying Objects Detection System Using Image Sensor,” INFORMATION AND COMMUNICATION TECHNOLOGY IN POLICING, vol. 2, no. 5 , pp. 65–77, 2021, [Online]. Available: https://sid.ir/paper/957435/en

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