Oil Spill Detection¶
Os principais sistemas de detecção e identificação da poluição marítima por hidrocarbonetos são os sensores de Radar de Abertura Sintética (SAR)
Refs¶
- Oil Spill Identification from Satellite Images Using Deep Neural Networks.
- Observing Marine Pollution with Synthetic Aperture Radar
- Compositional Oil Spill Detection Based on Object Detector and Adapted Segment Anything Model from SAR Images (2024)
- Semi-Supervised oil spill detection of SAR images based on pseudo-labelling (2024)
- Multiphysical Interpretable Deep Learning Network for Oil Spill Identification Based on SAR Images (2024)
- Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation
Dataset: Sensor: COSMO-SkyMed
Eyesea Method¶

Conclusions¶
- Current segmentation models are not trainable by fine tuning for this task
- combination of focal and dice loss have the best results for segmentation of oil spill
- Bigger datasets are key to improve this models