Research on a rapid recognition and classification system for household waste based on deep learning
ZHU Feng
Abstract：In order to improve the efficiency and accuracy of household waste treatment,the paper introduces the design and implementation of a rapid recognition and classification system for household waste based on deep learning,analyzes the application of deep learning technology in waste recognition and its feature extraction methods,and proposes a hardware selection scheme and application scenario construction strategy for the system.The research content includes garbage image recognition based on convolutional neural networks(CNN),multi-scale feature extraction and selection,hardware configuration of robotic arms and cameras,and the application of the system in garbage treatment plants,community garbage stations,and intelligent garbage bins.The recognition and classification efficiency and accuracy of the system were evaluated through the design of technical parameters in the testing environment.The research shows that the system shows significant advantages in intelligence,automation and networking,and provides a reference for the efficient classification and treatment of domestic waste.
Keywords：deep learningrapid identificationclassificationlife garbage
Publication Date：2025-05-25
Pages：4( 124-127 )