Automatic Crepe Rubber Grading System

Abstract

"In today's tech-driven world, a digital system for the rubber industry is essential for enhancing efficiency, productivity, and sustainability. By utilizing digital technologies and data analytics, this system aims to reduce human errors, improve grading accuracy, and optimize labor and time management. The demand for an automated grading system is evident, promising to streamline operations and improve both profitability and product quality. This study focuses on creating an automated Crepe Rubber grading system using Convolutional Neural Networks (CNNs), known for their effectiveness in image analysis. The CNNs were used to process and classify rubber images to automate the grading process."