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Deutsch Intern
    Chair of Computer Science VIII - Aerospace Information Technology

    SkyCam-5

    SkyCam-5 is a test platform for the autonomous detection of Unidentified Aerial Phenomena (UAP's). Through the use of image processing algorithms, the sky is continuously monitored for unusual phenomena. Current machine learning models are applied to reduce wrong detections. The main objective of the camera system is to detect UAP's. It can also detect short duration luminous phenomena such as lightning or meteors.  

     

     

    Fig.: Functionality of the Skycam-5 software for the detection of unknown phenomena

    Known objects such as birds, insects or helicopters are often detected in the camera's environment. These are detected and filtered out by a Convolutional Neural Network.

                                

    Fig.: Examples of detected objects