Work

Browser-based Object Detection System for Isolating Plastic Bottles Using the Coco-ssd Model

Year: 2024

Type: article

Abstract: Plastic waste, especially in urban environments and water bodies, poses a significant environmental threat. This paper presents a browser-based object detection system for identifying and isolating plastic bottles using state-of-the-art machine learning models. The system leverages TensorFlow.js, ML5.js, and P5.js libraries along with the COCO-SSD model to detect plastic bottles in real time using a mobile camera interface. By employing a browser-based architecture, the system offers cross-platform functionality, eliminating the need for server-based computations or specialized hardware. Experimental evaluation showed high detection accuracy across various environments, underscoring the potential for real-world applications in waste management and recycling efforts.

Source: International Journal of Advanced Research in Computer Science

DOI: 10.26483/ijarcs.v15i5.7124

Author: Chidozie Managwu

Institution: University of Bradford

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDGs: Responsible consumption and production, Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4403732919

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