Waste detection in Pomerania: non-profit project for detecting waste in environment

Waste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, either for economic or ecological reasons, and the industry demands high efficiency... Our team conducted comprehensive research on Artificial Intelligence usage in waste detection and classification to fight the world's waste pollution problem. As a result an open-source framework that enables the detection and classification of litter was developed. The final pipeline consists of two neural networks: one that detects litter and a second responsible for litter classification. Waste is classified into seven categories: bio, glass, metal and plastic, non-recyclable, other, paper and unknown. Our approach achieves up to 70% of average precision in waste detection and around 75% of classification accuracy on the test dataset. The code used in the studies is publicly available online. read more

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Results from the Paper


Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Object Detection Drinking Waste Classification EfficientDet-D2 AP50 99.4 # 1
Object Detection Extended TACO-1 EfficientDet-D2 AP50 56.8 # 1
Object Detection Extended TACO-7 EfficientDet-D2 mAP50 16.2 # 1
Object Detection MJU-Waste EfficientDet-D2 AP50 97.9 # 1
Object Detection UAVVaste EfficientDet-D2 AP50 74.1 # 1

Methods