Inside Defect Detection and Classification of Apple based on MRI Images

This dataset provides a high-quality collection of Magnetic Resonance Imaging (MRI) scans of Apple (fruit) samples designed for accurate internal defect detection and classification. It includes labeled images of both healthy and defective apples with diverse defect types. The dataset supports the development, training, and validation of advanced machine learning and deep learning models for non-destructive fruit quality assessment, post-harvest monitoring, and intelligent agricultural applications.