Аннотация
Currently used recycling technologies have limitations on the composition of recyclable waste, which makes them specialized. Thus, the preliminary sorting of municipal solid waste is a necessary step, increasing the efficiency of using municipal solid waste as a resource. To sort municipal solid waste we developed a method for detecting and classifying waste on a conveyor line using neural network image processing. Images from a camera are fed to a neural network input, which determines the position and type of detected objects. To train the neural network a database of more than 13,000 municipal solid waste images was created. Mean-Average Precision for the neural network model was 64%.
| Язык оригинала | английский |
|---|---|
| Номер статьи | 012127 |
| Число страниц | 7 |
| Журнал | Journal of Physics: Conference Series |
| Том | 1359 |
| Номер выпуска | 1 |
| DOI | |
| Состояние | Опубликовано - 21 ноя 2019 |
| Событие | 4th All-Russian Scientific Conference Thermophysics and Physical Hydrodynamics with the School for Young Scientists, TPH 2019 - Yalta, Crimea, Украина Продолжительность: 15 сен 2019 → 22 сен 2019 |
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Цитировать
Seredkin, A. V., Tokarev, M. P., Plohih, I. A., Gobyzov, O. A., & Markovich, D. M. (2019). Development of a method of detection and classification of waste objects on a conveyor for a robotic sorting system. Journal of Physics: Conference Series, 1359(1), [012127]. https://doi.org/10.1088/1742-6596/1359/1/012127