Intelligent system for solid waste classification using combination of image processing and machine learning models

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2024-02-28 DOI:10.1080/0952813x.2024.2323043

Hani Abu-Qdais, Nawras Shatnawi, Esra’a AL-Alamie

引用次数: 0

Abstract

Solid waste is a major issue in all cities around the world. Classification and segregation of solid waste prior to reuse, recycle or recover is an important step towards sustainable waste manageme...

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结合图像处理和机器学习模型的固体废物分类智能系统

固体废物是全世界所有城市都面临的一个重大问题。在再利用、再循环或回收之前对固体废物进行分类和分离是实现可持续废物管理的重要一步。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Experimental & Theoretical Artificial Intelligence 工程技术-计算机：人工智能

CiteScore

6.10

自引率

4.50%

发文量

审稿时长

>12 weeks

期刊介绍： Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving