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Research on Detection Algorithm of Foreign Object Debris and Small Targets in Airport Runway Based on SSD

Published: 17 May 2021 Publication History

Abstract

The SSD algorithm is currently a widely used target detection algorithm. In view of the small size of common foreign objects on airport runways and the low accuracy of SSD processing small target objects, this paper applies feature fusion method in SSD model to construct a new small target object detection algorithm model. The accuracy of the model is detected on the self-built airport runway foreign body data set, and the detection result mAP is 5% higher than the original SSD network.

References

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Redmon J, Divvala S, Girshick R, You only look once: Unified, real-time object detection [C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. LasVegas, USA: IEEE, 2016: 779-788.
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Liu W, Anguelov D, Erhan D, SSD: single shot multibox detector [C]//Proceed- ings of the 14th European Conference on Computer VisionECCV 2016. Netherlands: Springer International Publishing, 2016: 21-37.

Cited By

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  • (2024)The Modern Approaches for Identifying Foreign Object Debris (FOD) in Aviation2024 International Conference on Integrated Circuits and Communication Systems (ICICACS)10.1109/ICICACS60521.2024.10498909(1-5)Online publication date: 23-Feb-2024
  • (2024)Aircraft engine danger areas incursion detection using keypoint detection and IoTAlexandria Engineering Journal10.1016/j.aej.2024.03.00393(7-21)Online publication date: Apr-2024
  • (2022)A Comparison of Manual and Automotive FOD Detection Systems at Airport Runways2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)10.1109/ICRITO56286.2022.9964557(1-5)Online publication date: 13-Oct-2022
  • Show More Cited By

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    cover image ACM Other conferences
    CONF-CDS 2021: The 2nd International Conference on Computing and Data Science
    January 2021
    1142 pages
    ISBN:9781450389570
    DOI:10.1145/3448734
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 17 May 2021

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    Author Tags

    1. SSD
    2. airport runway
    3. foreign object debris
    4. object detection
    5. small target

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    CONF-CDS 2021

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    Cited By

    View all
    • (2024)The Modern Approaches for Identifying Foreign Object Debris (FOD) in Aviation2024 International Conference on Integrated Circuits and Communication Systems (ICICACS)10.1109/ICICACS60521.2024.10498909(1-5)Online publication date: 23-Feb-2024
    • (2024)Aircraft engine danger areas incursion detection using keypoint detection and IoTAlexandria Engineering Journal10.1016/j.aej.2024.03.00393(7-21)Online publication date: Apr-2024
    • (2022)A Comparison of Manual and Automotive FOD Detection Systems at Airport Runways2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)10.1109/ICRITO56286.2022.9964557(1-5)Online publication date: 13-Oct-2022
    • (2022)Enabling a Larger Deep Space Mission Suite: A Deep Space Network Queuing Antenna for Demand Access2022 IEEE Aerospace Conference (AERO)10.1109/AERO53065.2022.9843635(1-13)Online publication date: 5-Mar-2022
    • (2022)GeoMask : Foreign Object Debris Instance Segmentation Using Geodesic Representations2022 IEEE Aerospace Conference (AERO)10.1109/AERO53065.2022.9843628(1-9)Online publication date: 5-Mar-2022
    • (2022)Research on conflict detection model for taxi‐in process on the apron based on aircraft wingtip keypoint detectionIET Intelligent Transport Systems10.1049/itr2.1231417:5(878-896)Online publication date: 16-Nov-2022

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