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@article{165225,
        author = {Srikanth S and Dr. D. Sathya Srinivas},
        title = {FOREGIN OBJECT DETECTION IN AIRCRAFT RUNWAYS USING YOLO V3},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {11},
        number = {1},
        pages = {740-746},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=165225},
        abstract = {The FOD-R is a collection of images that depict common types of foreign object debris (FOD) that can be found on runways or taxiways. The dataset has primarily been annotated using bounding boxes to facilitate object detection. However, the FOD-xR Dataset consists of an extra feature - color codes - that offer facts on the benefit of eliminating the debris. Lightweight objects are marked in green, while heavy objects are marked in red. This centralized system simplifies coordination efforts, organization’s bottom line by minimizing delays and damage caused by FOD incidents. Overall, the FOD-R and FOD-xR Datasets are valuable re-assets for agencies seeking to decorate their FOD detection and removal processes. },
        keywords = {FOD-R, Bounding boxes, YOLO V3 Algorithm, Foreign Object Detection.},
        month = {},
        }