Remote Sensing Teacher: Cross-Domain Detection Transformer with Learnable Frequency-Enhanced Feature Alignment in Remote Sensing Imagery
J Han, W Yang, Y Wang, L Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Unsupervised domain adaptation (UDA) is critical for remote sensing object detection in real
applications, aiming to address the significant performance degradation issue caused by the …
applications, aiming to address the significant performance degradation issue caused by the …
Structured adversarial self-supervised learning for robust object detection in remote sensing images
Object detection plays a crucial role in scene understanding and has extensive practical
applications. In the field of remote sensing object detection, both detection accuracy and …
applications. In the field of remote sensing object detection, both detection accuracy and …
Neural Implicit Fourier Transform for Remote Sensing Shadow Removal
K Chi, J Li, W Jing, Q Li, Q Wang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Remote sensing shadow removal is an open issue. Previous studies focus on working in the
spatial dimension, ignoring the potential of the Fourier dimension, while illumination …
spatial dimension, ignoring the potential of the Fourier dimension, while illumination …
Enabling Near-Zero Cost Object Detection in Remote Sensing Imagery via Progressive Self-Training
X Zhang, X Jiang, Q Hu, H Luo, S Zhong… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
Deep learning-based object detection models rely heavily on large-scale and precise
annotations for training. However, manually annotating bounding-box annotations for such …
annotations for training. However, manually annotating bounding-box annotations for such …
Pseudo-Siamese Teacher for Semi-Supervised Oriented Object Detection
Oriented object detection, which aims at detecting objects with orientation properties, shows
great potential for visual analysis in complex scenarios, such as aerial images. However, the …
great potential for visual analysis in complex scenarios, such as aerial images. However, the …
Addressing Sample Inconsistency for Semi-Supervised Object Detection in Remote Sensing Images
Y Wang, L Yao, G Meng, X Zhang… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
The emergence of semisupervised object detection (SSOD) techniques has greatly
enhanced object detection performance. SSOD leverages a limited amount of labeled data …
enhanced object detection performance. SSOD leverages a limited amount of labeled data …