A pipeline for Solid Domestic Waste classification using Computer Vision

Daniel Otero Gomez, Santiago Cartagena Agudelo, Santiago Isaza Cadavid, Mauricio Toro and Juan Camilo Ramirez

No rvzyc, OSF Preprints from Center for Open Science

Abstract: This work aims to build and analyze a pipeline for solid domestic waste classification. The first steps that were carried out for this were to divide into three main lines that work together to achieve the pipeline. Each line used different sub-approaches to deep learning, relying on both the literature and the advisors, but without neglecting the binary classification work previously carried out. Additionally, a CRISP-DM methodology is taken into account to carry out the work without taking apart the mathematical concepts behind each computationally implemented method, and it is specified what are the intentions of the authors for the near future and their conclusions.

Date: 2021-11-19
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:rvzyc

DOI: 10.31219/osf.io/rvzyc

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