You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I want to propose a deep reinforcement learning-based controller for a quadcopter that tracks ground objects. The reward function should maximize the area of the bounding box of the target. I want to use mesh methods instead of the YOLO model for object detection in Airsim . Is this possible? because the yolo need a lot of computation
The text was updated successfully, but these errors were encountered:
I want to propose a deep reinforcement learning-based controller for a quadcopter that tracks ground objects. The reward function should maximize the area of the bounding box of the target. I want to use mesh methods instead of the YOLO model for object detection in Airsim . Is this possible? because the yolo need a lot of computation
The text was updated successfully, but these errors were encountered: