Autors: Yordanov, Y. E., Mladenov, V. M.
Title: Humanoid Robot Detecting Animals via Neural Network
Keywords: Aldebaran , NAO robot , Neural network , Python , Robot , Te

Abstract: The recognition of objects via neural networks is gaining increasing popularity and usability in the world around us. For example-in the production lines of the factories where the details are recognized and then automatically sorted, in the fully automated stores where the camera systems and deep learning algorithms recognize the products we take from shelves and adds them to a virtual shopping cart, in banks where robots recognize people's faces and offers them different services that the banks provide, or in the autonomous cars where it is needed quick and accurate recognition of the environment around the vehicles. This paper presents a neural network that can identify animals-with an existing set of pictures for training, it can recognize any animal. The pictures are taken from the robot's camera. They're then processed via a convolution neural network which is implemented via Tensorflow on a personal computer. As a result, the robot can identify and say the name of the animal st



    14th Symposium on Neural Networks and Applications (NEUREL), pp. 1-6, 2018, Serbia, IEEE, DOI 10.1109/NEUREL.2018.8587017

    Цитирания (Citation/s):
    1. Noboa Delgado, E.M., 2022. Sistema embebido para reconocimiento y conteo de esporas del hongo de género trichoderma mediante técnicas de visión artificial (Bachelor's thesis)., (Google Scholar) - 2022 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus и Web of Science