@donstu.ru
Don State Technical University
Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Mechanical Engineering
Scopus Publications
Denis Medvedev, Vyacheslav Grishhenko, Evgeniy Ivliev, Aleksandr Kharchenko, and Pavel Obukhov
AIP Publishing
Evgeniy Ivliev, Viktoria Demchenko, and Pavel Obukhov
Springer Singapore
Evgeniy Ivliev, Pavel Obukhov, Viktor Ivliev, Denis Medvedev, and Viktor Martynov
EDP Sciences
The article is devoted to the development and analysis of methods of identifying dynamic objects. A neural network with the architecture of SSD MobileNetV2 has been developed to solve the problem of detecting baggage tags and barcodes. Several approaches are considered to solve the problem of identifying digital-letter information: Tesseract, SSD InceptionV2, OpenCV and a convolutional neural network. The efficiency of the methods on real images was checked. It was concluded that electricity consumption can be reduced by 49.43%.
Denis Medvedev, Vyacheslav Grishhenko, Viktor Martynov, Evgeniy Ivliev, and Yurii Korol’kov
EDP Sciences
The article considers a method of controlling the motion of the output links of the tracking system of pneumatic actuators of technological equipment actuators. Dynamic and qualitative characteristics are improved by means of proportional-integral-differential (PID) controller. The mathematical model of actuator system, which includes power and control parts, has been developed. By calculation experiment the dynamic characteristics of the actuator have been obtained, from which it has been found possible to reduce the energy consumed by the actuator system to about 30%.
E A Ivliev and P S Obukhov
IOP Publishing
Abstract The article is devoted to the development and analysis of methods of identifying dynamic objects. A system for identifying information from a luggage tag based on several neural networks with the SSD InceptionV2 architecture has been developed. These neural networks work with sufficiently high accuracy 82-95% and speed 7-10fps. Advantages and disadvantages of application of method of scale-invariant feature transform for identification of luggage tags are considered. The operability of the methods on real images has been tested.