Region-based convolutional neural networks for object detection in very high resolution remote sensing images

2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016

Volumn , Issue , 2016, Pages 548-554

  Cao, Yushe ^a   Niu, Xin ^a   Dou, Yong ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

aircraft detection; convolutional neural network; deep learning; feature learning

Indexed keywords

AIRCRAFT DETECTION; COMPLEX NETWORKS; CONVOLUTION; FUZZY SYSTEMS; IMAGE RECONSTRUCTION; NEURAL NETWORKS; OBJECT DETECTION; OBJECT RECOGNITION;

BAG-OF-VISUAL-WORDS; COMPLEX ENVIRONMENTS; CONVOLUTIONAL NEURAL NETWORK; DEEP LEARNING; FEATURE LEARNING; HIGH RESOLUTION REMOTE SENSING IMAGES; REMOTE SENSING TECHNOLOGY; VERY HIGH RESOLUTION;

REMOTE SENSING;

EID: 84997770219     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FSKD.2016.7603232     Document Type: Conference Paper

References (14)

1. David G Lowe. Distinctive image features from scale-invariant keypoints. International journal of computer vision, 60(2):91-110, 2004.
2. Navneet Dalal and Bill Triggs. Histograms of oriented gradients for human detection. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 1, pages 886-893. IEEE, 2005.
3. Lorenzo Bruzzone and Lorenzo Carlin. A multilevel context-based system for classification of very high spatial resolution images. Geoscience and Remote Sensing, IEEE Transactions on, 44(9):2587-2600, 2006.
4. Hao Sun, Xian Sun, Hongqi Wang, Yu Li, and Xiangjuan Li. Automatic target detection in high-resolution remote sensing images using spatial sparse coding bag-of-words model. Geoscience and Remote Sensing Letters, IEEE, 9(1):109-113, 2012.
5. Wanceng Zhang, Xian Sun, Kun Fu, ChenyuanWang, and HongqiWang. Object detection in high-resolution remote sensing images using rotation invariant parts based model. Geoscience and Remote Sensing Letters, IEEE, 11(1):74-78, 2014.
6. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems, pages 1097-1105, 2012.
7. Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 580-587, 2014.
8. Jasper RR Uijlings, Koen EA van de Sande, Theo Gevers, and Arnold WM Smeulders. Selective search for object recognition. International journal of computer vision, 104(2):154-171, 2013.
9. Mayur Datar, Aristides Gionis, Piotr Indyk, and Rajeev Motwani. Maintaining stream statistics over sliding windows. SIAM Journal on Computing, 31(6):1794-1813, 2002.
10. C Lawrence Zitnick and Piotr Dollár. Edge boxes: Locating object proposals from edges. In Computer Vision-ECCV 2014, pages 391-405. Springer, 2014.
11. Ming-Ming Cheng, Ziming Zhang, Wen-Yan Lin, and Philip Torr. Bing: Binarized normed gradients for objectness estimation at 300fps. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 3286-3293, 2014.
12. D Huttenlocher and P Felzenszwalb. Efficient graph based image segmentation. IJCV, 59(2):167-181, 2004.
13. Corinna Cortes and Vladimir Vapnik. Support vector machine. Machine learning, 20(3):273-297, 1995.
14. Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. Region-based convolutional networks for accurate object detection and segmentation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 38(1):142-158, 2016.