Scalable multi-class geospatial object detection in high-spatial-resolution remote sensing images

By Gong Cheng, Junwei Han, Peicheng Zhou, Lei Guo. 2014

24 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

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

1. Gong Cheng
2. Junwei Han
3. Peicheng Zhou
4. Xiwen Yao
5. Chao Yao
6. Yanbang Zhang
7. Xiaoqiang Lu
8. Lei Guo

In Media Technology

1. Gong Cheng
2. Junwei Han
3. Peicheng Zhou
4. Xiwen Yao
5. Chao Yao
6. Yanbang Zhang
7. Lei Guo
8. Xiaoqiang Lu

Citations in the corpus

• A Survey on Object Detection in Optical Remote Sensing Images (2016, unknown): “…the last few years, SRC and its variants have been widely used in RSI analysis field, including geospatial object detection (Chen et al., 2011b, c; Cheng et al., 2014c; Han et al., 2014; Liu and Shi, 2014; Zhang et al., 2015c; Zhang et al., 2015d) and hyperspectral image classification (Chen et…”
• Object detection in VHR optical remote sensing images via learning rotation-invariant HOG feature (2016, background): “More recently, with the advances of machine learning, especially the powerful feature representations and classifiers, many approaches regarded object detection as a classification problem [1-22].”