Garbage Waste Classification Using Supervised Deep Learning Techniques

The management of solid waste in large urban environments has become a complex problem due to increasing amount of waste generated every day by citizens and companies. Current Computer Vision and Deep Learning techniques can help in the automatic detection and classification of waste types for further recycling tasks. Numerous data-driven methods for solving the problem are investigated in a realistic setting where most of the events are not actual emptying. Machine learning is an area with a huge potential for the transformation of many areas of life and science including industrial informatics. The investigated methods include the existing manually engineered model and its modification as well as conventional machines learning algorithms. This paper presents the use of automated machine learning for solving a practical problem of a real-life Smart Waste Management system.