Autors: Pleshkova, S. G., Bekyarski, A. B., Zahariev, Z. T.
Title: Based on Artificial Intelligence and Deep Learning Hand Gesture Recognition for Interaction with Mobile Robots
Keywords: Communication skills, Hand gestureHand-gesture recognition, Home application, Human interactions, Real timeTechnical complexit

Abstract: The proliferation of mobile robots in a wide range of professional and home applications is a real stimulus of researches for more convenient natural ways and communication skills of mobile robots to interact with human. Voice communicating with mobile robots is always preferable but in many cases is inappropriate due to technical complexity, not enough accuracy and inability of real time of voice recognition. That is why voice communications with mobile robots are often replaced or combined with human interaction by hand gestures. Therefore, this is the goal of this article, with proposition of realization based on artificial intelligence and deep learning



    10th National Conference with International Participation, 16 May 2019 through 17 May 2019, vol. ELECTRONICA 2019 - Proceedings, issue 10, pp. Article number 8825611, 2019, Bulgaria, Institute of Electrical and Electronics Engineers Inc., DOI 10.1109/ELECTRONICA.2019.8825611

    Цитирания (Citation/s):
    1. Zeqi YuWei Qi Yan.Human Action Recognition Using Deep Learning Methods.November 2020 DOI: 10.1109/IVCNZ51579.2020.9290594 Conference: 2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ) - 2020 - в издания, индексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus