Addressing Sample Inconsistency for Semisupervised Object Detection in Remote Sensing Images
The emergence of semisupervised object detection (SSOD) techniques has greatly enhanced object detection performance. SSOD leverages a limited amount of labeled data along with a large quantity of unlabeled data. However, there exists a problem of sample inconsistency in remote sensing images, which...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
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Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10463140/ |