Part 9/17:
Data Sources: Cameras (IP, CCTV, drones, mobile devices), videos, or robotics provide raw inputs.
Pre-Processing: Standard techniques adapt images for neural network input, including downscaling, lighting correction, background subtraction, or activity-based filtering.
Model Inference: Selected models—based on use case constraints—perform object detection, classification, or recognition tasks.
Post-Processing & Insights: Results are mapped onto real-world interpretations such as inventory status, compliance verification, or security alerts.
Action & Feedback: Insights trigger operational responses—alerting staff, logging discrepancies, or automating decisions—and feedback is used to improve models.