Land cover classification based on SAR and optical images using ensemble machine learning
Land cover classification is an important remote sensing application. Satellite optical and radar images are two of the most widely used remote sensing images with respective advantages and disadvantages. Using both radar and optical images and machine learning, this project is to explore automatic...
Main Author: | Tian, Gege |
---|---|
Other Authors: | Lu Yilong |
Format: | Final Year Project (FYP) |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/158216 |
Similar Items
-
Land cover classification with satellite optical and radar image fusion
by: Zhu, Di
Published: (2019) -
Land cover classification using satellite optical and radar image fusion
by: Liu, Yunwei
Published: (2019) -
Low-shot machine learning for medical image classification
by: Yip, Chun Mun
Published: (2020) -
Cross-modality learning for earth surface mapping with cloud-covered satellite optical images and radar images
by: Pi, Ziyi
Published: (2021) -
Development of an ensemble of extreme learning machines for 3D medical object segmentation and classification
by: Tan, Zu Ming.
Published: (2012)