An object-based supervised classification framework for very-high-resolution remote sensing images using convolutional neural networks
Author:
Affiliation:
1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China
Funder
LIESMARS Special Research Funding
Fundamental Research Funds for the Central Universities
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)
Link
https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2017.1422873
Reference26 articles.
1. The Relationship Between Variable Selection and Data Agumentation and a Method for Prediction
2. Geographic Object-Based Image Analysis – Towards a new paradigm
3. Unsupervised Feature Learning for Aerial Scene Classification
4. Support-vector networks
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