Measuring the Effectiveness of Various Features for Thematic Information Extraction From Very High Resolution Remote Sensing Imagery
By X. Chen, Tao Fang, Hong Huo, Deren Li. 2015
28 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
- Liangpei Zhang
- Xiaoqiang Lu
- Gui-Song Xia
- Xiang Bai
- Yanfei Zhong
- Baoguang Shi
- Luisa Verdoliva
- Junwei Han
In Media Technology
- Liangpei Zhang
- Xiaoqiang Lu
- Gui-Song Xia
- Yanfei Zhong
- Xiang Bai
- Jingwen Hu
- Baoguang Shi
- Luisa Verdoliva
Citations in the corpus
- Land Use Classification in Remote Sensing Images by Convolutional Neural Networks (2015, background): “In [30], instead, feature selection is performed separately for each class, with both one-versus-all and one-versus-one strategies.”
- AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification (2016, methodology): “developed to select a good subset of low-level visual features for aerial image classification [27].”