Identification of the Multiconnection Uncertainty Dynamic Objects Based on Neural Networks

2022 ◽  
pp. 496-504
Author(s):  
S. M. Jafarov ◽  
A. S. Aliyeva
Keyword(s):  
Neural Networks ◽  
Dynamic Objects

scholarly journals Improving the energy efficiency of sorting centers by identifying objects and digit-letter information with neural networks

2021 ◽  
Vol 279 ◽  
pp. 01017
Author(s):  
Evgeniy Ivliev ◽  
Pavel Obukhov ◽  
Viktor Ivliev ◽  
Denis Medvedev ◽  
Viktor Martynov
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Energy Efficiency ◽  
Convolutional Neural Network ◽  
Electricity Consumption ◽  
Dynamic Objects

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%.

scholarly journals NEURAL NETWORKS IN THE MANAGEMENT OF COMPLEX TECHNICAL SYSTEMS

2019 ◽  
Vol 40 (2) ◽  
pp. 68-72
Author(s):  
R.L Panteev
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Neural Control ◽  
Advantages And Disadvantages ◽  
The Neural Networks ◽  
Complex Technical Systems ◽  
Technical Systems ◽  
Dynamic Objects ◽  
Methods Of Application

The methods of application of neural networks for solving the problems of control of dynamic objects are considered. For each type of neural control, the circuits for connecting the neural networks within the control system are presented and the procedures for their training are described in detail. The advantages and disadvantages of the described methods are analyzed.

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