A Systematic Review of CNN Architectures and Evaluation Metrics in Solid Waste Classification Using Deep Learning

Jorge Isaac Necochea-Chamorro

doi:10.18421/TEM152-81

A Systematic Review of CNN Architectures and Evaluation Metrics in Solid Waste Classification Using Deep Learning

Jorge Isaac Necochea-Chamorro

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	1927-1942
Number of pages	16
Journal	TEM Journal
Volume	15
Issue number	2
DOIs	https://doi.org/10.18421/TEM152-81
State	Published - 27 May 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 12 Responsible Consumption and Production

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10.18421/TEM152-81

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@article{079afc44ae4f4580b908ed537db28635,

title = "A Systematic Review of CNN Architectures and Evaluation Metrics in Solid Waste Classification Using Deep Learning",

keywords = "architectures, classification, convolutional neural network, Deep learning, metrics, solid waste",

author = "Necochea-Chamorro, \{Jorge Isaac\}",

note = "Publisher Copyright: {\textcopyright} 2026 Jorge Isaac Necochea-Chamorro; published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License.",

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KW - architectures

KW - classification

KW - convolutional neural network

KW - Deep learning

KW - metrics

KW - solid waste

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A Systematic Review of CNN Architectures and Evaluation Metrics in Solid Waste Classification Using Deep Learning

UN SDGs

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