Image Segmentation

May, 2021

Semantic Segmentation on Aerial Drone Images using U-Net addresses the developing automation in aerial drone piloting and image capturing. While current automation is not yet ripe, with the manual operation still needed, we decided to run image semantic segmentation on aerial drone-captured images to automate and refine the object detection in drone operation. This project first uses U-Net and then advances to Mobile-Unet as the primary machine learning approach towards solving the problem. Our model yields satisfactory results with the implementation of the high-performance model (in both computational time and accuracy) and by fine-tuning the model and self-creating testing datasets.

Please see [https://github.com/MstXy/ML_final_project] for more details.

Thank you!