Abstract
The software complex “Auto-Elevator” aimed at automating the unloading and loading of grain at the elevator is considered. The software package is written in C# and allows solving two problems: automatic detection of a free port for unloading grain and the use of an autopilot to supply a vehicle to a loading or unloading terminal. To determine the boundaries of the parking space or to determine a free port for unloading grain, image recognition using neural networks consisting of basic blocks is used. The basic blocks are assembled in the same way as the constructor, by adding layer by layer. The main blocks of convolutional neural networks are convolutional layers, subsampling (pooling) layers, activation layers, and fully connected layers. A convolutional layer extracts features in the input image and generates a feature map.
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Popov, S., Galchenko, G., Marchenko, J., Drozdov, D. (2022). Use of Neural Networks and Autopilot for Quick and Accurate Grain Discharge on the Elevator. In: Shamtsyan, M., Pasetti, M., Beskopylny, A. (eds) Robotics, Machinery and Engineering Technology for Precision Agriculture. Smart Innovation, Systems and Technologies, vol 247. Springer, Singapore. https://doi.org/10.1007/978-981-16-3844-2_6
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