Hybrid AI approach predicts fruit freshness with over 90% accuracy

Researchers have developed a hybrid approach using image processing and machine learning to predict fruit quality, specifically identifying freshness. The system combines an image processing algorithm that quantifies spoilage with a convolutional neural network (CNN) for binary classification. By synthesizing the outputs of these methods with logistic regression, the system achieves over 90% accuracy in distinguishing fresh from rotten apples and oranges. A key advantage is its real-time performance without high computational demands, though it currently requires fruits to be isolated against a white or transparent background. AI

IMPACT This hybrid AI and image processing method offers a practical, real-time solution for agricultural quality control, potentially reducing food waste.

RANK_REASON The cluster contains an academic paper detailing a novel methodology. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

• Amir Reza Hashemi
• arXiv
• Malus
• The Oranges

• paper
• product
• other

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