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Application of YOLO algorithm on student UAV

The main concern of this paper will be to explain the workflow of YOLO2 and YOLO3 object detection algorithms with regards to training on custom dataset for the purpose of deploying said algorithms on NVIDIA Jetson mini board that is placed inside the shell of an unmanned aerial vehicle made for a purpose of student unmanned aerial vehicle(SUAV) competition. A walk through the key concepts and intuition regarding neural nets, typical data augmentation processes, the training process and deployment, both from software and hardware point of view, will be given.

YOLO , YOLOv2 , YOLOv3 , MATLAB , Python , Object detection application , UAV

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