Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Industrial Computer Vision for Government
- Overview of machine vision systems in manufacturing environments
- Common defects: cracks, scratches, misalignments, missing components
- Artificial intelligence versus traditional rule-based visual inspection methods
Image Acquisition and Preprocessing for Government
- Types of cameras and image capture settings
- Techniques for noise reduction, contrast enhancement, and normalization
- Data augmentation strategies to enhance training robustness
Object Detection and Segmentation Techniques for Government
- Classical approaches: thresholding, edge detection, contour analysis
- Deep learning methods: Convolutional Neural Networks (CNNs), U-Net, YOLO
- Criteria for selecting between detection, classification, and segmentation techniques
Defect Detection Model Development for Government
- Preparing annotated datasets for training
- Training defect classifiers and segmenters
- Evaluating model performance using precision, recall, and F1-score metrics
Deployment in Industrial Settings for Government
- Hardware considerations: GPUs, edge devices, industrial PCs
- Architecture of real-time inspection pipelines
- Integration with Programmable Logic Controllers (PLCs) and factory automation systems
Performance Tuning and Maintenance for Government
- Managing changing lighting conditions and production environments
- Strategies for model retraining and continual learning
- Implementing alerting, logging, and quality assurance (QA) reporting systems
Case Studies and Domain Applications for Government
- Defect detection in automotive assembly and welding processes
- Surface inspection in electronics and semiconductor manufacturing
- Label and packaging verification in pharmaceuticals and food production
Summary and Next Steps for Government
Requirements
- Experience with machine learning or computer vision concepts
- Familiarity with Python programming
- Basic understanding of quality control or industrial automation
Audience
- Quality assurance teams for government
- Automation engineers
- Computer vision developers
14 Hours
