/SAR_yolov3

Best Accruacy:speed ratio SAR Ship detection in the world.

Primary LanguagePython

SAR_yolov3

Welcome to SAR SHIP DETECTION

We have applied YOLO-V3 Object detection on SAR Satellite Images. We are detecting ship by these Images where SAR sensors are immune to bad weather and night time which a great way of detecting . We applied YOLO-V3 to it and it gives best accuracy:speed ratio in the world among all other models and methods applied. We are further looking to improve the accuracy where the current accuracy is 90.25 %.

Files

We have included the Config file which is the model architecture for the darknet deep learning framework where we changed the models in many ways for our results , from data augmentation to hyper-parameters. Anchors boxes is also given in this repositories. Some scripts which converted the VOC Xml into Darknet Text Format

Results

Prediction 1

PREDICTION 1

Prediction 2

PREDICTION 1

Submission

We have written a research paper on this project and submitted into a Springer conference.