BROWSER-BASED OBJECT DETECTION SYSTEM FOR ISOLATING PLASTIC BOTTLES USING THE COCO-SSD MODEL

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Chidozie Managwu
Daniel Matthias

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.

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Author Biography

Daniel Matthias, Department of Computer Science, Rivers State University, Port Harcourt, Nigeria

Department of Computer Science,
Rivers State University,
Port Harcourt, Nigeria