A Deep Curriculum Learning Semi-Supervised Framework for Remote Sensing Scene Classification
In recent years, deep learning has witnessed astonishing success in the field of remote sensing in images. Generally, deep learning requires a large amount of labeled training data. Nevertheless, in remote sensing, sufficient labeled data are scarce because labeled data are often difficult, expensiv...
Saved in:
Main Authors: | Qing Zhang, Jialu Chen, Baohua Yuan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/1/360 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
UKSSL: Underlying Knowledge Based Semi-Supervised Learning for Medical Image Classification
by: Zeyu Ren, et al.
Published: (2024-01-01) -
DRCO: Dense-Label Refinement and Cross Optimization for Semi-Supervised Object Detection
by: Yunlong Qin, et al.
Published: (2025-01-01) -
A Semi-Supervised Learning Approach to Quality-Based Web Service Classification
by: Mehdi Nozad Bonab, et al.
Published: (2024-01-01) -
Safeguards-related event detection in surveillance video using semi-supervised learning approach
by: Se-Hwan Park, et al.
Published: (2025-02-01) -
Study of implicit information semi-supervised learning algorithm
by: Guo-dong LIU, et al.
Published: (2015-10-01)