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Detection of arbitrarily rotated objects is a challenging task due to the difficulties of locating the multi-angle objects and separating them effectively from the background.
Object detection with discriminatively trained part-based models
P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan · 2010
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Automatic target detection in high-resolution remote sensing images using spatial sparse coding bag-of-words model
H. Sun, X. Sun, H. Wang, Y. Li, and X. Li · 2012
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Airborne vehicle detection in dense urban areas using hog features and disparity maps
S. Tuermer, F. Kurz, P. Reinartz, and U. Stilla · 2013
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Selective search for object recognition
J. R. Uijlings, K. E. Van De Sande, T. Gevers, and A. W. Smeulders · 2013
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Vehicle detection in satellite images by hybrid deep convolutional neural networks
X. Chen, S. Xiang, C.-L. Liu, and C.-H. Pan · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
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Edge boxes: Locating object proposals from edges
C. L. Zitnick and P. Dollár · 2014
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Fast r-cnn
R. Girshick · 2015
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Object detection in optical remote sensing images based on weakly supervised learning and high-level feature learning
J. Han, D. Zhang, G. Cheng, L. Guo, and J. Ren · 2015
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Deep neural networks-based vehicle detection in satellite images
Q. Jiang, L. Cao, M. Cheng, C. Wang, and J. Li · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
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Vehicle detection in high-resolution aerial images based on fast sparse representation classification and multiorder feature
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Vehicle detection in high-resolution aerial images via sparse representation and superpixels
Z. Chen, C. Wang, C. Wen, X. Teng, Y. Chen, H. Guan, H. Luo, L. Cao, and J. Li · 2016
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Learning rotation-invariant convolutional neural networks for object detection in vhr optical remote sensing images
G. Cheng, P. Zhou, and J. Han · 2016
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You only look once: Unified, real-time object detection
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi · 2016
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Convolutional neural network based automatic object detection on aerial images
I. Ševo and A. Avramović · 2016
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Weakly supervised learning based on coupled convolutional neural networks for aircraft detection
F. Zhang, B. Du, L. Zhang, and M. Xu · 2016
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Building regional covariance descriptors for vehicle detection
X. Chen, R.-X. Gong, L.-L. Xie, S. Xiang, C.-L. Liu, and C.-H. Pan · 2017
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K. He, G. Gkioxari, P. Dollár, and R. Girshick · 2017
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Accurate object localization in remote sensing images based on convolutional neural networks
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R-fcn: Object detection via region-based fully convolutional networks
J. Dai, Y. Li, K. He, and J. Sun · 2016
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Efficient saliency-based object detection in remote sensing images using deep belief networks
W. Diao, X. Sun, X. Zheng, F. Dou, H. Wang, and K. Fu · 2016
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Feature pyramid networks for object detection
T.-Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan, and S. Belongie · 2016
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Ssd: Single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A. C. Berg · 2016
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Y. Long, Y. Gong, Z. Xiao, and Q. Liu · 2017
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Fast deep vehicle detection in aerial images
L. W. Sommer, T. Schuchert, and J. Beyerer · 2017
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Affine invariant description and large-margin dimensionality reduction for target detection in optical remote sensing images
L. Wan, L. Zheng, H. Huo, and T. Fang · 2017
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Oriented response networks
Y. Zhou, Q. Ye, Q. Qiu, and J. Jiao · 2017
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