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Course Outline
Introduction to Industrial Computer Vision for Government
- Overview of machine vision systems in manufacturing environments for government
- Common defects identified by these systems: cracks, scratches, misalignments, and missing components
- Comparison between AI-driven and traditional rule-based visual inspection methods for government applications
Image Acquisition and Preprocessing for Government
- Types of cameras and image capture settings suitable for government use
- Techniques for noise reduction, contrast enhancement, and normalization in government settings
- Data augmentation strategies to enhance the robustness of training models for government applications
Object Detection and Segmentation Techniques for Government
- Classical approaches: thresholding, edge detection, and contour analysis
- Advanced deep learning methods: Convolutional Neural Networks (CNNs), U-Net, and YOLO
- Criteria for selecting between object detection, classification, and segmentation techniques in government contexts
Defect Detection Model Development for Government
- Preparing annotated datasets for training models in government settings
- Training defect classifiers and segmenters tailored for government needs
- Evaluating model performance using metrics such as precision, recall, and F1-score for government applications
Deployment in Industrial Settings for Government
- Hardware considerations for deployment: GPUs, edge devices, and industrial PCs suitable for government use
- Architecture of real-time inspection pipelines designed for government operations
- Integration with Programmable Logic Controllers (PLCs) and factory automation systems in government facilities
Performance Tuning and Maintenance for Government
- Strategies for managing changing lighting and production conditions in government settings
- Processes for model retraining and continual learning to ensure ongoing accuracy for government applications
- Implementation of alerting, logging, and quality assurance (QA) reporting systems integrated into government operations
Case Studies and Domain Applications for Government
- Defect detection in automotive assembly and welding processes for government projects
- Surface inspection of electronics and semiconductors used in government systems
- Label and packaging verification in pharmaceutical and food industries regulated by government agencies
Summary and Next Steps for Government
Requirements
- Experience with machine learning or computer vision concepts for government applications
- Familiarity with Python programming
- Basic understanding of quality control or industrial automation processes
Audience
- Quality Assurance (QA) teams
- Automation engineers
- Computer vision developers
14 Hours
