https://www.selleckchem.com/pr....oducts/gusacitinib.h
Accurate waste classification is key to successful waste management. However, most current studies have focused exclusively on single-label waste classification from images, which goes against common sense. In this paper, we move beyond single-label waste classification and propose a benchmark for evaluating the multi-label waste classification and localization tasks to advance waste management via deep learning-based methods. We propose a multi-task learning architecture (MTLA) based on a convolutional neural network, which can be
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