Tomato Quality Classification Based on Transfer Learning Feature Extraction and Machine Learning Algorithm Classifiers
Hassan Shabani Mputu,
Ahmed Abdel-Mawgood,
Atsushi Shimada
et al.
Abstract:The demand for high-quality tomatoes to meet consumer and market standards, combined with large-scale production, has necessitated the development of an inline quality grading. Since manual grading is time-consuming, costly, and requires a substantial amount of labor. This study introduces a novel approach for tomato quality sorting and grading, focusing specifically on the color feature of tomato images. The method leverages pre-trained convolutional neural networks (CNNs) for feature extraction and tradition… Show more
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