Artificial Intelligence #waste classification#deep learning
EcoBin Neural Network Cuts Waste Sorting Errors by Detecting Contamination in Recyclables
EcoBin is a two-stage deep convolutional neural network that classifies household waste and explicitly accounts for contamination. The first stage achieves 87.42% test accuracy and 96.13% pathway-adjusted accuracy, while the contamination stage distinguishes clean from contaminated items with a 0.99 ROC-AUC. On contaminated recyclables, the full pipeline correctly routes 24 of 25 items, a significant improvement over the base classifier alone.
Jun 16, 2026 1 source