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 |