Scattering-point-guided RPN for oriented ship detection in SAR images
Y Zhang, D Lu, X Qiu, F Li - Remote Sensing, 2023 - mdpi.com
Ship detection in synthetic aperture radar (SAR) images has attracted widespread attention
due to its significance and challenges. In recent years, numerous detectors based on deep …
due to its significance and challenges. In recent years, numerous detectors based on deep …
UAVPNet: A balanced and enhanced UAV object detection and pose recognition network
P Shan, R Yang, H Xiao, L Zhang, Y Liu, Q Fu, Y Zhao - Measurement, 2023 - Elsevier
With the increasing popularity of unmanned aerial vehicles (UAVs), accurate positioning and
pose recognition of UAVs by target images based on photoelectric detection become a …
pose recognition of UAVs by target images based on photoelectric detection become a …
Lightweight and anchor-free frame detection strategy based on improved CenterNet for multiscale ships in SAR images
H Xie, X Jiang, J Zhang, J Chen, G Wang… - Frontiers in Computer …, 2022 - frontiersin.org
Ship detection using synthetic aperture radar (SAR) images has important applications in
military and civilian fields, but the different sizes of the ship downgrade the detection …
military and civilian fields, but the different sizes of the ship downgrade the detection …
MBAHIL: design of a multimodal hybrid bioinspired model for augmentation of hyperspectral imagery via iterative learning for continuous efficiency enhancements
The augmentation of hyperspectral images requires the design of high-density feature
analysis & band-fusion models that can generate multimodal imagery from limited …
analysis & band-fusion models that can generate multimodal imagery from limited …
Scene-aware data augmentation for ship detection in SAR images
Y Tang, S Wang, J Wei, Y Zhao, J Lin… - International Journal of …, 2024 - Taylor & Francis
Ship detection in synthetic aperture radar (SAR) images is widely applied in marine
monitoring. In recent years, convolutional neural networks (CNNs) have made significant …
monitoring. In recent years, convolutional neural networks (CNNs) have made significant …