Statement on the security threat posed by unmanned aerial systems and possible countermeasures Oversight and Management Efficiency Subcommittee, Homeland Security Committee, 2015. ,
Exploring Civil Drone Accidents and Incidents to Help Prevent Potential Air Disasters, Aerospace, vol.4, issue.3, p.22, 2016. ,
DOI : 10.1016/j.aap.2015.01.021
URL : http://www.mdpi.com/2226-4310/3/3/22/pdf
Observations from above: unmanned aircraft systems and privacy, Harv. JL & Pub. Pol'y, vol.36, p.457, 2013. ,
Towards detection and control of civilian unmanned aerial vehicles, 2013. ,
Advanced Doppler radar physiological sensing technique for drone detection, SPIE Defense+ Security. International Society for Optics and Photonics, 2017. ,
DOI : 10.1117/12.2262758
Drone detection and classification methods and apparatus, U.S. Patent No, vol.275, issue.9 1, p.645, 2016. ,
Analyzing the threat of unmanned aerial vehicles (UAV) to nuclear facilities, Security Journal, vol.8, issue.3???4, pp.1-20, 2017. ,
DOI : 10.1007/s12198-015-0161-y
Vision-based detection and distance estimation of micro unmanned aerial vehicles, Sensors, vol.15, issue.9, pp.23805-23846, 2015. ,
Shape-based image retrieval using generic Fourier descriptor, Signal Processing: Image Communication, vol.17, issue.10, pp.825-848, 2002. ,
DOI : 10.1016/S0923-5965(02)00084-X
Flexible, high performance convolutional neural networks for image classification, IJCAI Proceedings- International Joint Conference on Artificial Intelligence, 2011. ,
Best practices for convolutional neural networks applied to visual document analysis, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings., 2003. ,
DOI : 10.1109/ICDAR.2003.1227801
Deep cross-domain flying object classification for robust UAV detection Advanced Video and Signal Based Surveillance (AVSS), 14th IEEE International Conference on, 2017. ,
DOI : 10.1109/avss.2017.8078558
A study on detecting drones using deep convolutional neural networks Advanced Video and Signal Based Surveillance (AVSS), 14th IEEE International Conference on, 2017. ,
DOI : 10.1109/avss.2017.8078541
Using deep networks for drone detection Advanced Video and Signal Based Surveillance (AVSS), 14th IEEE International Conference on, 2017. ,
DOI : 10.1109/avss.2017.8078539
URL : http://arxiv.org/pdf/1706.05726
Ordered minimum distance bag-of-words approach for aerial object identification Advanced Video and Signal Based Surveillance (AVSS), 14th IEEE International Conference on, 2017. ,
Bag-of-visual-words and spatial extensions for land-use classification, Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS '10, 2010. ,
DOI : 10.1145/1869790.1869829
Introduction to the bag of features paradigm for image classification and retrieval, 2011. ,
Human Behavior Recognition based on Conditional Random Field and Bag-Of-Visual-Words Semantic Model, International Journal of Signal Processing, Image Processing and Pattern Recognition, vol.8, issue.1, pp.23-32, 2015. ,
DOI : 10.14257/ijsip.2015.8.1.03
Shape discrimination using Fourier descriptors, IEEE Transactions on systems, man, and cybernetics, vol.73, pp.170-179, 1977. ,
DOI : 10.1109/tsmc.1977.4309681
Effective Gaussian mixture learning for video background subtraction, IEEE transactions on pattern analysis and machine intelligence, vol.275, pp.827-832, 2005. ,
Background subtraction techniques: a review, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2004. ,
DOI : 10.1109/ICSMC.2004.1400815
Seeded region growing, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.16, issue.6, pp.641-647, 1994. ,
DOI : 10.1109/34.295913