ship-classification

The official implementation of P^2Net (Push-and-Pull Network) for fine-grained ship classification in remote sensing images

Deep Learning for SAR Ship classification: Focus on Unbalanced Datasets and Inter-Dataset Generalization

For this project, we will complete ship classification using the Sentinel-1 and OpenSar ship datasets with a CNN used for large scale image recognition

Python Code for SCRC-Net: A Structure-Constrained and Representation-Consistent Network for SAR Ship Classification

AIMGroup is marine cargo ship surveyors and consultant with expertise on class and risk managing on seaworthiness and tecnical condition.

Modular deep-learning pipeline for SAR ship detection, three-class vessel classification, cross-dataset analysis, and metadata-style maritime reporting.

Code, results and leak-free splits for auditing incidence-angle effects in Sentinel-1 SAR foundation models (SSL4EO-S12, SoftCon, TerraMind) on ship and iceberg classification: angle leakage on the Statoil/C-CORE benchmark and confounded range shifts on OpenSARShip.

SAR Limitations evaluator