Development of a method of detection and classification of waste objects on a conveyor for a robotic sorting system

A. V. Seredkin, M. P. Tokarev, I. A. Plohih, O. A. Gobyzov, D. M. Markovich

Research output: Contribution to journalConference articlepeer-review

Abstract

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%.

Original languageEnglish
Article number012127
Number of pages7
JournalJournal of Physics: Conference Series
Volume1359
Issue number1
DOIs
Publication statusPublished - 21 Nov 2019
Event4th All-Russian Scientific Conference Thermophysics and Physical Hydrodynamics with the School for Young Scientists, TPH 2019 - Yalta, Crimea, Ukraine
Duration: 15 Sep 201922 Sep 2019

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