[1] Han J W, Zhang D W, Cheng G et al. Object detection in optical remote sensing images based on weakly supervised learning and high-level feature learning[J]. IEEE Transactions on Geoscience and Remote Sensing, 53, 3325-3337(2015). http://ieeexplore.ieee.org/document/6991537

[2] Cheng G, Han J W. A survey on object detection in optical remote sensing images[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 117, 11-28(2016). http://arxiv.org/abs/1603.06201v1

[3] Cheng G, Han J W, Zhou P C et al. Multi-class geospatial object detection and geographic image classification based on collection of part detectors[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 98, 119-132(2014). http://www.sciencedirect.com/science/article/pii/S0924271614002524

[4] Deng Z P, Sun H, Zhou S L et al. Multi-scale object detection in remote sensing imagery with convolutional neural networks[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 145, 3-22(2018).

[5] Zhong Y F, Han X B, Zhang L P. Multi-class geospatial object detection based on a position-sensitive balancing framework for high spatial resolution remote sensing imagery[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 138, 281-294(2018). http://www.sciencedirect.com/science/article/pii/S0924271618300492

[6] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 60, 91-110(2004). http://doi.ieeecomputersociety.org/resolve?ref_id=doi:10.1023/B:VISI.0000029664.99615.94&rfr_id=trans/tp/2008/10/ttp2008101683.htm

[7] Dalal N, Triggs B. Histograms of oriented gradients for human detection. [C]∥2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), June 20-25, 2005, San Diego, CA, USA. New York: IEEE, 8588935(2005).

[8] Felzenszwalb P. McAllester D, Ramanan D. A discriminatively trained, multiscale, deformable part model. [C]∥2008 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2008, Anchorage, AK, USA. New York: IEEE, 10139902(2008).

[9] Fu C Y, Liu W, Ranga A et al. -01-23)[2019-04-07]. https: ∥arxiv., org/abs/1701, 06659(2017).

[10] Lin T Y, Goyal P, Girshick R et al. Focal loss for dense object detection. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 2999-3007(2017).

[11] Zhang S F, Wen L Y, Bian X et al. Single-shot refinement neural network for object detection. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 4203-4212(2018).

[12] Chen Z, Zhang T, Ouyang C. End-to-end airplane detection using transfer learning in remote sensing images[J]. Remote Sensing, 10, 139(2018).

[13] Liu W, Anguelov D, Erhan D et al. SSD: single shot multibox detector[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9905, 21-37(2016).

[14] Xia G S, Bai X, Ding J et al. DOTA: a large-scale dataset for object detection in aerial images. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 3974-3983(2018).

[15] Redmon J, Farhadi A. YOLO9000: better, faster, stronger. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 6517-6525(2017).

[16] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks. [C]∥Advances in Neural Information Processing Systems 28(NIPS 2015), December 7-12, 2015, Palais des Congrès de Montréal, Montréal Canada. Canada: NIPS, 91-99(2015).

[17] He K M, Gkioxari G, Dollar P et al. Mask R-CNN. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 2980-2988(2017).

[18] Lin T Y, Dollar P, Girshick R et al. Feature pyramid networks for object detection. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 936-944(2017).

[19] Cai Z W, Vasconcelos N. Cascade R-CNN: delving into high quality object detection. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 6154-6162(2018).

[20] Han X B, Zhong Y F, Zhang L P. An efficient and robust integrated geospatial object detection framework for high spatial resolution remote sensing imagery[J]. Remote Sensing, 9, 666(2017).

[21] Ren Z J, Lin S Z, Li D W et al. Mask R-CNN object detection method based on improved feature pyramid[J]. Laser & Optoelectronics Progress, 56, 041502(2019).

[22] Zhu M M, Xu Y L, Ma S P et al. Airport detection method with improved region-based convolutional neural network[J]. Acta Optica Sinica, 38, 0728001(2018).

[23] Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation. [C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 3431-3440(2015).

[24] Chen L C, Papandreou G, Kokkinos I, fully connected CRFs[J/OL] et al. -06-07)[2019-04-07]. https: ∥arxiv., org/abs/1412, 7062(2016).

[25] Cheng G, Zhou P C, Han J W. Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing, 54, 7405-7415(2016). http://ieeexplore.ieee.org/document/7560644

[26] Dai J F, Li Y, He K M et al. R-FCN: object detection via region-based fully convolutional networks. [C]∥Advances in Neural Information Processing Systems 29(NIPS 2016), December 5-10, 2016, Centre Convencions Internacional Barcelona, Barcelona Spain. Canada: NIPS, 379-387(2016).

[27] Dai J F, Qi H Z, Xiong Y W et al. Deformable convolutional networks. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 764-773(2017).

[28] Deng Z P, Sun H, Lei L et al. Object detection in remote sensing imagery with multi-scale deformable convolutional networks[J]. Acta Geodaetica et Cartographica Sinica, 47, 1216-1227(2018).