Abstract

Fruit grading systems are critical for ensuring the quality, consistency, and efficiency of fruit production and distribution. These systems utilize advanced technologies such as computer vision and automation to accurately identify and classify fruit based on various quality parameters such as size, colour, and blemishes. The use of automated grading systems reduces the need for manual labour, increases throughput, and improves accuracy by minimizing human error. This results in a faster and more efficient grading process that can handle large volumes of fruit quickly and consistently, reducing the time and cost of fruit grading. Additionally, fruit grading systems play a crucial role in reducing waste and promoting sustainability in the fruit industry. By accurately grading fruit, less high-quality fruit goes to waste, and resources are used more efficiently. Grading systems can also identify opportunities for optimization, such as reducing packaging waste or identifying areas for process improvement. Overall, fruit grading systems are essential for ensuring high-quality fruit that meets the demands of the industry while also promoting sustainability and efficient distribution. Key Words: Object Detection, Computer Vision, Machine Learning, Deep Learning, Fruit Grading, TensorFlow.

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