A multi-model ensemble method based on convolutional neural networks for aircraft detection in large remote sensing images-Reference-Cited by-同舟云学术

A multi-model ensemble method based on convolutional neural networks for aircraft detection in large remote sensing images

Published:2017-10-25 Issue:1 Volume:9 Page:11-20
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Zhang Yuhang¹²,Fu Kun¹,Sun Hao¹,Sun Xian¹,Zheng XinWei¹^ORCID,Wang Hongqi¹

Affiliation:

1. Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, China

2. School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2017.1378452

Reference7 articles.

1. Efficient Saliency-Based Object Detection in Remote Sensing Images Using Deep Belief Networks

2. Deep Residual Learning for Image Recognition

3. What Makes for Effective Detection Proposals?

4. Aircraft Recognition in High-Resolution Satellite Images Using Coarse-to-Fine Shape Prior

5. Automatic Target Detection in High-Resolution Remote Sensing Images Using Spatial Sparse Coding Bag-of-Words Model

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