《A Novel Detector Based on Convolution Neural Networks for Multiscale SAR Ship Detection in Complex》
A Novel Detector Based on Convolution Neural Networks for Multiscale SAR Ship Detection in Complex Background 20204月發表在sensors上 文章提出，現有的模型在複雜背景下檢測多尺度艦船目標和小目標時效果並不令人滿意，因此，基於CNN提出一種新型SAR艦船檢測，包含三個分支結構，融合
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相關文章
- 1. 《A Multilayer Fusion Light-Head Detector for SAR Ship Detection》
- 2. Deep Learning Meets SAR
- 3. Cascade-based attacks on complex networks
- 4. Automatic Ship Detection in Optical Remote Sensing Images Based on Anomaly Detection and SPP-PCANet
- 5. Visual saliency detection based on multiscale deep cnn features
- 6. Paper Notes: A Comprehensive Survey on Graph Neural Networks
- 7. 【全部譯文】Deep-Waveform: A Learned OFDM Receiver Based on Deep Complex Convolutional Networks
- 8. A guide to receptive field arithmetic for Convolution Neural Networks
- 9. How convolution neural networks work
- 10. HIERARCHICAL MULTISCALE RECURRENT NEURAL NETWORKS