Review and Evaluation of Deep Learning Architectures for Efficient Land Cover Mapping with UAS Hyper-Spatial Imagery: A Case Study Over a Wetland

Review and Evaluation of Deep Learning Architectures for Efficient Land Cover Mapping with UAS Hyper-Spatial Imagery: A Case Study Over a Wetland

Deep learning has already been proved as a powerful state-of-the-art technique for many image understanding tasks in computer vision and other applications including remote sensing (RS) image analysis. Unmanned aircraft systems (UASs) offer a viable and economical alternative to a conventional senso...

Full description

Bibliographic Details
Main Authors: Mohammad Pashaei, Hamid Kamangir, Michael J. Starek, Philippe Tissot
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Remote Sensing
Subjects:
coastal wetland
land cover mapping
semantic image segmentation
machine learning
deep learning
convolutional neural networks
transfer learning
unmanned aircraft systems
Online Access:https://www.mdpi.com/2072-4292/12/6/959

Internet

https://www.mdpi.com/2072-4292/12/6/959

Similar Items