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paper-defect

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poetabdullah / Paper-Defect-Detection-and-Classification

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This project automates paper defect localization in industrial quality control using feature extraction and machine learning. Techniques include HOG, Gabor filters, Canny edge detection, and Wavelet Transform with SVMs, CNNs, and ensemble learning. It aims to reduce manual inspection, improving efficiency and reliability in defect detection.

machine-learning computer-vision feature-selection feature-extraction image-classification feature-engineering classification-model surface-detection industry-automation paper-defect
  • Updated Sep 4, 2025

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