FOD-A: A Dataset for Foreign Object Debris in Airports

Federal Aviation Administration, “Airport foreign object debris detection equipment,” Federal Aviation Administration, Tech. Rep., 09 2009, advisory circular: 150/5220-24

2009

Earlier work this paper cites.

J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A large-scale hierarchical image database,” in 2009 IEEE Conference on Computer Vision and Pattern Recognition , 2009, pp. 248–255

2009

Earlier work this paper cites.

Federal Aviation Administration, “Airport foreign object debris management,” Federal Aviation Administration, Tech. Rep., 09 2010, advisory circular: 150/5210-24

2010

Earlier work this paper cites.

E. Herricks, P. Lazar, E. Woodworth, and J. Patterson, “Performance assessment of a mobile, radar-based foreign object debris detection system,” University of Illinois and Federal Aviation Administration, Tech. Rep., 09 2011

2011

Earlier work this paper cites.

E. Herricks, E. Woodworth, S. Majumdar, and J. Patterson, “Performance assessment of a radar-based foreign object debris detection system,” University of Illinois and Federal Aviation Administration, Tech. Rep., 02 2011

2011

Earlier work this paper cites.

E. Herricks, P. Lazar, E. Woodworth, and J. Patterson, “Performance assessment of an electro-optical-based foreign object debris detection system,” University of Illinois and Federal Aviation Administration, Tech. Rep., 03 2012

2012

Earlier work this paper cites.

E. Herricks, E. Woodworth, and J. Patterson, “Performance assessment of a hybrid radar and electro-optical foreign object debris detection system,” University of Illinois and Federal Aviation Administration, Tech. Rep., 05 2012

2012

Earlier work this paper cites.

M. Alexander-Adams, “Fact sheet – foreign object debris (fod),” https://www.faa.gov/news/fact_sheets/news_story.cfm?newsId=15394 , Nov 2013

2013

Earlier work this paper cites.

T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick, “Microsoft coco: Common objects in context,” in Proceedings of European Conference on Computer Vision . Springer, 2014, pp. 740–755

2014

Cited alongside, same era.

R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Rich feature hierarchies for accurate object detection and semantic segmentation,” 2014

2014

Cited alongside, same era.

M. Everingham, S. M. A. Eslami, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman, “The pascal visual object classes challenge: A retrospective,” International Journal of Computer Vision , vol. 111, no. 1, pp. 98–136, Jan. 2015

2015

Cited alongside, same era.

W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. E. Reed, C. Fu, and A. C. Berg, “SSD: single shot multibox detector,” CoRR , vol. abs/1512.02325, 2015. [Online]. Available: http://arxiv.org/abs/1512.02325

Original

2015

Cited alongside, same era.

M. Sandler, A. Howard, M. Zhu, A. Zhmoginov, and L.-C. Chen, “Mobilenetv2: Inverted residuals and linear bottlenecks,” 2019

2019

Later among the works it cites.

Z.-D. Yuan, J.-Q. Li, Z.-N. Qiu, and Y. Zhang, “Research on FOD detection system of airport runway based on artificial intelligence,” Journal of Physics: Conference Series , vol. 1635, p. 012065, nov 2020. [Online]. Available: https://doi.org/10.1088/1742-6596/1635/1/012065

2020

Later among the works it cites.

P. Li and H. Li, “Research on fod detection for airport runway based on yolov3,” in 2020 39th Chinese Control Conference (CCC) , 2020, pp. 7096–7099

2020

Later among the works it cites.

“Computer Vision Annotation Tool,” https://github.com/openvinotoolkit/cvat, 2021, last accessed on July 1

2021

Closest in time.

C. G. Northcutt, A. Athalye, and J. Mueller, “Pervasive label errors in test sets destabilize machine learning benchmarks,” 2021