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Deep learning methods have made significant progress in ship detection in synthetic aperture radar (SAR) images.
“Wide-area traffic monitoring with the sar/gmti system pamir,”
Delphine Cerutti-Maori, Jens Klare, Andreas R Brenner, and Joachim HG Ender, · 2008
Earlier work this paper cites.
“Ship surveillance with terrasar-x,”
Stephan Brusch, Susanne Lehner, Thomas Fritz, Matteo Soccorsi, Alexander Soloviev, and Bart van Schie, · 2010
Earlier work this paper cites.
“Deep convolutional neural networks for lvcsr,”
Tara N Sainath, Abdel-rahman Mohamed, Brian Kingsbury, and Bhuvana Ramabhadran, · 2013
Earlier work this paper cites.
“Multilayer cfar detection of ship targets in very high resolution sar images,”
Biao Hou, Xingzhong Chen, and Licheng Jiao, · 2014
Earlier work this paper cites.
“Very deep convolutional networks for large-scale image recognition,”
Karen Simonyan and Andrew Zisserman, · 2014
Earlier work this paper cites.
“Faster r-cnn: Towards real-time object detection with region proposal networks,”
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun, · 2015
Earlier work this paper cites.
“Imagenet large scale visual recognition challenge,”
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Fei-Fei Li, · 2015
Earlier work this paper cites.
“Fast r-cnn,”
Ross Girshick, · 2015
Earlier work this paper cites.
“Scheme of parameter estimation for generalized gamma distribution and its application to ship detection in sar images,”
Gui Gao, Kewei Ouyang, Yongbo Luo, Sheng Liang, and Shilin Zhou, · 2016
Earlier work this paper cites.
“Projection shape template-based ship target recognition in terrasar-x images,”
Jiwei Zhu, Xiaolan Qiu, Zongxu Pan, Yueting Zhang, and Bin Lei, · 2016
Earlier work this paper cites.
“Ssd: Single shot multibox detector,”
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C Berg, · 2016
Earlier work this paper cites.
“You only look once: Unified, real-time object detection,”
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi, · 2016
Earlier work this paper cites.
“Deep residual learning for image recognition,”
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, · 2016
Earlier work this paper cites.
“Learning rotation-invariant convolutional neural networks for object detection in vhr optical remote sensing images,”
Gong Cheng, Peicheng Zhou, and Junwei Han, · 2016
Earlier work this paper cites.
“Mask r-cnn,”
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick, · 2017
Cited alongside, same era.
“Focal loss for dense object detection,”
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár, · 2017
Cited alongside, same era.
“Feature pyramid networks for object detection,”
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie, · 2017
Cited alongside, same era.
“Ship detection in sar images based on an improved faster r-cnn,”
Jianwei Li, Changwen Qu, and Jiaqi Shao, · 2017
Cited alongside, same era.
“Linking image and text with 2-way nets,”
Aviv Eisenschtat and Lior Wolf, · 2017
Cited alongside, same era.
“Soft-nms–improving object detection with one line of code,”
Navaneeth Bodla, Bharat Singh, Rama Chellappa, and Larry S Davis, · 2017
Cited alongside, same era.
“Saliency-guided single shot multibox detector for target detection in sar images,”
Lan Du, Lu Li, Di Wei, and Jiashun Mao, · 2019
Later among the works it cites.
“Depthwise separable convolution neural network for high-speed sar ship detection,”
Tianwen Zhang, Xiaoling Zhang, Jun Shi, and Shunjun Wei, · 2019
Later among the works it cites.
“High-speed ship detection in sar images based on a grid convolutional neural network,”
Tianwen Zhang and Xiaoling Zhang, · 2019
Later among the works it cites.
“Drbox-v2: An improved detector with rotatable boxes for target detection in sar images,”
Quanzhi An, Zongxu Pan, Lei Liu, and Hongjian You, · 2019
Later among the works it cites.
“Task-driven common representation learning via bridge neural network,”
Yao Xu, Xueshuang Xiang, and Meiyu Huang, · 2019
Later among the works it cites.
“Weighted boxes fusion: ensembling boxes for object detection models,”
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“Cascade r-cnn: Delving into high quality object detection,”
Zhaowei Cai and Nuno Vasconcelos, · 2018
Cited alongside, same era.
“A densely connected end-to-end neural network for multiscale and multiscene sar ship detection,”
Jiao Jiao, Yue Zhang, Hao Sun, Xue Yang, Xun Gao, Wen Hong, Kun Fu, and Xian Sun, · 2018
Cited alongside, same era.
“Squeeze and excitation rank faster r-cnn for ship detection in sar images,”
Zhao Lin, Kefeng Ji, Xiangguang Leng, and Gangyao Kuang, · 2018
Cited alongside, same era.
“Dota: A large-scale dataset for object detection in aerial images,”
Gui-Song Xia, Xiang Bai, Jian Ding, Zhen Zhu, Serge Belongie, Jiebo Luo, Mihai Datcu, Marcello Pelillo, and Liangpei Zhang, · 2018
Cited alongside, same era.
“Yolov3: An incremental improvement,”
Joseph Redmon and Ali Farhadi, · 2018
Cited alongside, same era.
“Identifying corresponding patches in sar and optical images with a pseudo-siamese cnn,”
Lloyd H Hughes, Michael Schmitt, Lichao Mou, Yuanyuan Wang, and Xiao Xiang Zhu, · 2018
Cited alongside, same era.
Roman Solovyev, Weimin Wang, and Tatiana Gabruseva, · 2019
Later among the works it cites.
“Air-sarship–1.0: High resolution sar ship detection dataset,”
S Xian, W Zhirui, S Yuanrui, D Wenhui, Z Yue, and F Kun, · 2019
Later among the works it cites.
“Learning roi transformer for oriented object detection in aerial images,”
Jian Ding, Nan Xue, Yang Long, Gui-Song Xia, and Qikai Lu, · 2019
Later among the works it cites.
“Yolov4: Optimal speed and accuracy of object detection,”
Alexey Bochkovskiy, Chien-Yao Wang, and Hong-Yuan Mark Liao, · 2020
Later among the works it cites.
“Precise and robust ship detection for high-resolution sar imagery based on hr-sdnet,”
Shunjun Wei, Hao Su, Jing Ming, Chen Wang, Min Yan, Durga Kumar, Jun Shi, and Xiaoling Zhang, · 2020
Later among the works it cites.
“Attention receptive pyramid network for ship detection in sar images,”
Yan Zhao, Lingjun Zhao, Boli Xiong, and Gangyao Kuang, · 2020
Later among the works it cites.
“An anchor-free method based on feature balancing and refinement network for multiscale ship detection in sar images,”
Jiamei Fu, Xian Sun, Zhirui Wang, and Kun Fu, · 2020
Later among the works it cites.
“R2fa-det: Delving into high-quality rotatable boxes for ship detection in sar images,”
Shiqi Chen, Jun Zhang, and Ronghui Zhan, · 2020
Later among the works it cites.
“Hrsid: A high-resolution sar images dataset for ship detection and instance segmentation,”
Shunjun Wei, Xiangfeng Zeng, Qizhe Qu, Mou Wang, Hao Su, and Jun Shi, · 2020
Later among the works it cites.