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Machine Vision and Intelligent Algorithm Based on Neural Network.

Meng Li1, Tiebo Sun1

  • 1Department of Mechanical and Electrical Engineering, Jiangsu Food & Pharmaceutical Science College, Huaian 223001, Jiangsu, China.

Computational Intelligence and Neuroscience
|March 21, 2022
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Summary
This summary is machine-generated.

This study optimizes neural networks for machine vision, achieving 99.28% accuracy in metal defect detection. The ICS-BP algorithm demonstrates superior convergence speed for intelligent algorithms.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Machine Learning

Background:

  • Neural network algorithms and intelligent algorithms are key areas in deep learning research.
  • Machine vision environments require robust image recognition capabilities.

Purpose of the Study:

  • To optimize neural network and intelligent algorithms for enhanced machine vision.
  • To improve target image recognition in simulation experiments.
  • To evaluate the performance of optimized algorithms in practical applications.

Main Methods:

  • Application of neural networks in machine vision is introduced.
  • An improved VGG-16 convolutional neural network (CNN) model was used for metal block defect detection.
  • Intelligent algorithms based on neural networks, including BP, PSO-BP, and an improved neural network algorithm (ICS-BP), were studied using the CIFAR-10 dataset.

Main Results:

  • The optimized VGG-16 CNN model achieved a maximum accuracy of 99.28% in classifying metal block defects.
  • The ICS-BP algorithm exhibited the fastest convergence speed, reaching convergence at 32 iterations.
  • The PSO-BP algorithm showed a slower convergence rate compared to ICS-BP.

Conclusions:

  • The optimized neural network algorithms significantly enhance target image recognition in machine vision.
  • The ICS-BP algorithm presents a highly efficient approach for intelligent algorithm convergence.
  • The study demonstrates the effectiveness of deep learning techniques in industrial defect detection and algorithm optimization.