Latest Research in Advanced Neural Network Applications

Top Research Topics in Advanced Neural Network Applications

• Advanced Neural Network Applications — 8 papers
• Advanced SAR Imaging Techniques — 6 papers
• Synthetic Aperture Radar (SAR) Applications and Techniques — 3 papers
• Computer Vision and Pattern Recognition — 3 papers
• Infrared Target Detection Methodologies — 2 papers
• Image and Video Processing — 2 papers
• Image Enhancement Techniques — 2 papers
• Adversarial Robustness in Machine Learning — 1 papers
• Advanced Image Processing Techniques — 1 papers
• Welding Techniques and Residual Stresses — 1 papers

Highest-Cited Papers

1. A physical Scattering-Guided Prior-Enhanced Mamba model for high-fidelity SAR ship generation in complex backgrounds
2. ARMOR: Robust and Efficient CNN-Based S AR ATR through Mo del-Ha r dware Co-Design
3. Adaptive Spatial–Frequency Information Fusion for SAR Ship Detection
4. Prototype-Driven Semantic Tree with Bimodal Embedding Space for Zero-Shot SAR Ship Recognition
5. Shape-Prior Dynamic Refinement Network with Diffusion Wavelets for Fine-Grained Ship Detection in Remote Sensing Images
6. Underwater multi-sensor information fusion for salient object detection
7. Fifty Years of SAR Automatic Target Recognition: The Road Forward
8. Constrained Boundary Enhancement for SAM 2-Based Ship Segmentation in UAV Berthing and Unberthing Videos
9. Physics-Aware Deep Learning for SAR and InSAR Remote Sensing: Models, Methods, and Open Challenges
10. A Two-Stage Framework for SAR Near-Shore Ship Detection via Segmentation Guidance and Enhanced Diffusion
11. A Robust Maritime Visual Perception Framework via Dual-Branch Wavelet Fusion and Feature-Enhanced YOLOv8n
12. OSSDD - a New Open Dataset for Sentinel-1 Ship Detection
13. Enhancing ship recognition in satellite imagery: a YOLO-centric framework based on the updated ShipRSImageNet benchmark
14. VSTF-Net: A Vision-Semantic and Target-Aware Fusion Framework for Ship Detection in Complex Maritime Sensing Scenarios
15. YOLO-CPCL: Compact Multi-Class Oriented Ship Detection with Adaptive Feature Fusion and Aspect-Ratio-Coupled Angle Supervision
16. Retrieval-assisted feature fusion of SAR image and bounce-coded RCS for aircraft classification
17. Semi-Supervised Structural Prior-Guided Network for Space Target Component Segmentation in ISAR Images
18. Direction-adaptive Mamba: Spatial-Frequency Dual-Domain Collaborative Learning for PolSAR Image Classification
19. CD-TrGNN: A Complex-Domain Transformer–Graph Neural Network for ISAR Space Target Attitude Estimation
20. An Improved Recognition Technique for Ship Targets Based on Dual-Path Cooperative Fusion Mechanism