Comparative Analysis of Learning-Based Approaches for Change Detection in Satellite Images
Satellite image change detection, where two images of the same area from different times are compared, is crucial for earth sensing and monitoring applications. Many learning-based detection methods have been proposed for this task, with different performance characteristics. Since these detection m...
Saved in:
Main Authors: | Maria-Eirini Pegia, Bjorn or Jonsson, Anastasia Moumtzidou, Ilias Gialampoukidis, Stefanos Vrochidis, Ioannis Kompatsiaris |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10815622/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
SFSCDNet: A Deep Learning Model With Spatial Flow-Based Semantic Change Detection From Bi-Temporal Satellite Images
by: K. S. Basavaraju, et al.
Published: (2024-01-01) -
Tropical cyclone intensity estimation based on YOLO-NAS using satellite images in real time
by: Priyanka Nandal, et al.
Published: (2025-02-01) -
Utilizing Implicit User Feedback to Improve Interactive Video Retrieval
by: Stefanos Vrochidis, et al.
Published: (2011-01-01) -
Implementing an Outgoing Longwave Radiation Climate Dataset from Fengyun 3E Satellite Data with a Machine-Learning Algorithm
by: Yanjiao Wang, et al.
Published: (2025-01-01) -
Deep Convolutional Network Based Machine Intelligence Model for Satellite Cloud Image Classification
by: Kalyan Kumar Jena, et al.
Published: (2023-03-01)