Browsing by Author "Kuzmenko, Nataliia"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    MINIMIZATION OF UNMANNED AERIAL VEHICLE TRAJECTORY DEVIATION DURING THE COMPLICATED OBSTACLES OVERFLY
    (National Aviation University Proceedings, 2012) Kharchenko, Volodymyr; Kuzmenko, Nataliia; Харченко, Володимир Петрович
    In the article the important problems of Unmanned Aerial Vehicle collision avoidance have been discussed. The model of Unmanned Aerial Vehicle movement was described. The principle of complicated form of the obstacle overfly trajectory creation has been represented. An overfly of the restricted area at the aeronautical chart was shown.
  • No Thumbnail Available
    Item
    PROBABILISTIC APPROACH TO OBJECT DETECTION AND RECOGNITION FOR VIDEOSTREAM PROCESSING
    (Вісник Національного Авіаційного Університету, 2017) Харченко, Володимир Петрович; Kharchenko, Volodymyr; Kukush, Alexander; Кукуш, О.Г.; Kuzmenko, Nataliia; Кузьменко, Н.С.; Ostroumov, Ivan; Остроумов, І.В.
    Purpose: The represented research results are aimed to improve theoretical basics of computer vision and artificial intelligence of dynamical system. Proposed approach of object detection and recognition is based on probabilistic fundamentals to ensure the required level of correct object recognition. Methods: Presented approach is grounded at probabilistic methods, statistical methods of probability density estimation and computer-based simulation at verification stage of development. Results: Proposed approach for object detection and recognition for video stream data processing has shown several advantages in comparison with existing methods due to its simple realization and small time of data processing. Presented results of experimental verification look plausible for object detection and recognition in video stream. Discussion: The approach can be implemented in dynamical system within changeable environment such as remotely piloted aircraft systems and can be a part of artificial intelligence in navigation and control systems.