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This repository hosts a case study on Transfer Learning aimed at improving the accuracy of metal nut inspection systems. The project explores the practical application of Transfer Learning methods to optimize quality control in the manufacturing industry, providing valuable insights into their effectiveness and potential benefits.

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MahanPourhosseini/Metal-Nut-Defect-Detection

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Problem Statement

Automated inspection and defect detection systems use AI to inspect manufacturing parts for failures and defects. They are used across industries to detect flaws on manufactured surfaces such as metallic rails, semiconductor wafers, and contact lenses. Here are some examples of how companies are using automated inspection systems:

  1. To detect defects in multiple elements of the aircraft
  2. To inspect bevel gears used in automotive parts
  3. To detect surface defects, missing parts, and cracks in railway facility components such as rails, sleepers, and fasteners

Automated Optical Inspection (AOI) System

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This repository hosts a case study on Transfer Learning aimed at improving the accuracy of metal nut inspection systems. The project explores the practical application of Transfer Learning methods to optimize quality control in the manufacturing industry, providing valuable insights into their effectiveness and potential benefits.

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