Multilabel classification of UAV images with Convolutional Neural Networks

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 2016-November, Issue , 2016, Pages 5083-5086

  Zeggada, Abdallah ^a   Melgani, Farid ^a  

^a UNIVERSITY OF TRENTO   (Italy)

Author keywords

coarse description; extremely high resolution; image analysis; image multilabeling; multi object detection; unmanned aerial vehicle

Indexed keywords

EID: 85007462360     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2016.7730325     Document Type: Conference Paper

References (13)

1. "Nonproliferation: Agencies could improve information sharing and end-use monitoring on unmanned aerial vehicle exports," Jul, 2012
2. F. S. Leira, T. A. Johansen and T. I. Fossen, "Automatic detection, classification and tracking of objects in the ocean surface from UAVs using a thermal camera," 2015 IEEE Aerospace Conference, Big Sky, MT, 2015, pp. 1-10
3. C. Luo, J. Nightingale, E. Asemota and C. Grecos, "A UAVCloud System for Disaster Sensing Applications," 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), Glasgow, 2015, pp. 1-5
4. S. Li, H. Tang, S. He, Y. Shu, T. Mao, J. Li, Z. Xu, "Unsupervised Detection of Earthquake-Triggered Roof-Holes From UAV Images Using Joint Color and Shape Features," in IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 9, pp. 1823-1827, Sept. 2015
5. T. Moranduzzo and F. Melgani, "Detecting Cars in UAV Images With a Catalog-Based Approach," in IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 10, pp. 6356-6367, Oct. 2014
6. T. Moranduzzo, F. Melgani, Y. Bazi, and N. Alajlan, "A fast object detector based on high-order gradients and Gaussian process regression for uav images," International Journal of Remote Sensing, vol. 36, no. 10, pp. 2713-2733, 2015
7. T. Moranduzzo, M. L. Mekhalfi and F. Melgani, "LBP-based multiclass classification method for UAV imagery," 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, 2015, pp. 2362-2365
8. Y. Lecun, L. Bottou, Y. Bengio and P. Haffner, "Gradient-based learning applied to document recognition," in Proceedings of the IEEE, vol. 86, no. 11, pp. 2278-2324, Nov 1998
9. C. Szegedy, L. Wei, J. Yangqing , P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, A. Rabinovich, "Going deeper with convolutions," 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, 2015, pp. 1-9
10. S. Zheng, S. Jayasumana, B. Romera-Paredes, V. Vineet, Z. Su, D. Du, C. Huang, P. H. S. Torr, "Conditional Random Fields as Recurrent Neural Networks," 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, 2015, pp. 1529-1537
11. Christopher M. Bishop, Neural Networks for Pattern Recognition, p. 164-190, Clarendon Press, 1995
12. R. F. Nogueira, R. de Alencar Lotufo and R. Campos Machado, "Fingerprint Liveness Detection Using Convolutional Neural Networks," in IEEE Transactions on Information Forensics and Security, vol. 11, no. 6, pp. 1206-1213, June 2016
13. N. Tajbakhsh, J. Y. Shin, S. R. Gurudu, R. T. Hurst, C. B. Kendall, M. B. Gotway, J. Liang, "Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning," in IEEE Transactions on Medical Imaging, vol. 35, no. 5, pp. 1299-1312, May 2016.