Deformable Feature Fusion and Accurate Anchors Prediction for Lightweight SAR Ship Detector Based on Dynamic Hierarchical Model Pruning
In recent years, convolutional neural networks (CNNs) have been extensively utilized for synthetic aperture radar (SAR) ship detection tasks. The fixed square shape of convolutional kernels in traditional convolutional limits the ability to extract features. Moreover, the large number of parameters...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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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/11016180/ |
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