Gradient Boosting Machine and Object-Based CNN for Land Cover Classification

Gradient Boosting Machine and Object-Based CNN for Land Cover Classification

In regular convolutional neural networks (CNN), fully-connected layers act as classifiers to estimate the probabilities for each instance in classification tasks. The accuracy of CNNs can be improved by replacing fully connected layers with gradient boosting algorithms. In this regard, this study in...

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Bibliographic Details
Main Authors: Quang-Thanh Bui, Tien-Yin Chou, Thanh-Van Hoang, Yao-Min Fang, Ching-Yun Mu, Pi-Hui Huang, Vu-Dong Pham, Quoc-Huy Nguyen, Do Thi Ngoc Anh, Van-Manh Pham, Michael E. Meadows
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
object-based image analysis
gradient boosting
convolutional neural network
land cover
Online Access:https://www.mdpi.com/2072-4292/13/14/2709

Internet

https://www.mdpi.com/2072-4292/13/14/2709

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