Intelligent Classification of Different Types of Plastics using Deep Transfer Learning

被引：3

作者：

Chazhoor, Anthony Ashwin Peter ^{[1
]}

Zhu, Manli ^{[1
]}

Ho, Edmond S. L. ^{[1
]}

Gao, Bin ^{[2
]}

Woo, Wai Lok ^{[1
]}

机构：

[1] Northumbria Univ, Dept Comp & Informat Sci, Newcastle Upon Tyne NE1 8ST, Tyne & Wear, England

[2] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu, Peoples R China

来源：

PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ROBOTICS, COMPUTER VISION AND INTELLIGENT SYSTEMS (ROBOVIS) | 2021年

关键词：

Deep Learning; Transfer Learning; Image Classification; Recycling;

D O I：

10.5220/0010716500003061

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Plastic pollution has affected millions globally. Research shows tiny plastics in the food we eat, the water we drink, and even in the air, we breathe. An average human intakes 74,000 micro-plastic every year, which significantly affects the health of living beings. This pollution must be administered before it severely impacts the world. We have substantially compared three state-of-the-art models on the WaDaBa dataset, which contains different types of plastics. These models are capable of classifying different types of plastic wastes which canbe reused or recycled, thus limiting their wastage.

引用

页码：190 / 195

页数：6

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