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SAR Ship Detection
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Ship detection based on SAR images
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
R-Sparse R-CNN: SAR Ship Detection Based on Background-Aware Sparse Learnable Proposals
Multitask Learning for SAR Ship Detection with Gaussian-Mask Joint Segmentation
A Visual Question Answering Method for SAR Ship: Breaking the Requirement for Multimodal Dataset Construction and Model Fine-Tuning
RSNet: A Light Framework for The Detection of SAR Ship Detection
AMANet: Advancing SAR Ship Detection with Adaptive Multi-Hierarchical Attention Network
Ship Detection in SAR Images with Human-in-the-Loop
Sar Ship Detection based on Swin Transformer and Feature Enhancement Feature Pyramid Network
SAR-ShipNet: SAR-Ship Detection Neural Network via Bidirectional Coordinate Attention and Multi-resolution Feature Fusion
Context-Preserving Instance-Level Augmentation and Deformable Convolution Networks for SAR Ship Detection
Two-Parameter CFAR Ship Detection Algorithm Based on Rayleigh Distribution in SAR Images
Learning Polar Encodings for Arbitrary-Oriented Ship Detection in SAR Images
Boosting ship detection in SAR images with complementary pretraining techniques
The QXS-SAROPT Dataset for Deep Learning in SAR-Optical Data Fusion
Balance Scene Learning Mechanism for Offshore and Inshore Ship Detection in SAR Images
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.