Unseen Land Cover Classification from High-Resolution Orthophotos Using Integration of Zero-Shot Learning and Convolutional Neural Networks

Unseen Land Cover Classification from High-Resolution Orthophotos Using Integration of Zero-Shot Learning and Convolutional Neural Networks

Zero-shot learning (ZSL) is an approach to classify objects unseen during the training phase and shown to be useful for real-world applications, especially when there is a lack of sufficient training data. Only a limited amount of works has been carried out on ZSL, especially in the field of remote...

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Bibliographic Details
Main Authors: Biswajeet Pradhan, Husam A. H. Al-Najjar, Maher Ibrahim Sameen, Ivor Tsang, Abdullah M. Alamri
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
land cover classification
deep-learning
CNN
Zero-Shot Learning
remote sensing
orthophotos
Online Access:https://www.mdpi.com/2072-4292/12/10/1676

Internet

https://www.mdpi.com/2072-4292/12/10/1676

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