A generic discriminative part-based model for geospatial object detection in optical remote sensing images
By Wanceng Zhang, Xian Sun, Hongqi Wang, Kun Fu. 2015
53 citations recorded by the source corpus.
Subfields: Atmospheric Science, Computer Vision and Pattern Recognition, Media Technology, Remote Sensing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Zhenfeng Shao
- Weixun Zhou
- Congmin Li
- Shawn D. Newsam
- Liangpei Zhang
- Junwei Han
- Gong Cheng
- Gui-Song Xia
In Media Technology
- Zhenfeng Shao
- Weixun Zhou
- Congmin Li
- Shawn D. Newsam
- Liangpei Zhang
- Gong Cheng
- Junwei Han
- Gui-Song Xia
In Remote Sensing
- Zhenfeng Shao
- Weixun Zhou
- Congmin Li
- Shawn D. Newsam
- Keiller Nogueira
- Otávio Augusto Bizetto Penatti
- J. A. D. Santos
- Lionel Gueguen
Citations in the corpus
- A Survey on Object Detection in Optical Remote Sensing Images (2016, unknown): “…(Chen et al., 2011a, 2013; Qian et al., 2013; Tao et al., 2012), and object detection in RSIs (Chen et al., 2011b, c; Cheng et al., 2014c; Du and Zhang, 2014; Han et al., 2014; Liu and Shi, 2014; Yokoya and Iwasaki, 2015; Zhang et al., 2014a; Zhang et al., 2015c; Zhang et al., 2015d).”
- PatternNet: A Benchmark Dataset for Performance Evaluation of Remote Sensing Image Retrieval (2017, methodology): “For object detection in remote sensing images, several extensions of HOG have been developed in order to improve detection performance [64– 67].”