📊 Model Evaluation
Model Evaluation
Evaluate AI models correctly — with the right metrics for industrial vision applications
mAP
Detection Metric
F1
Classification
IoU
Segmentation
Key Features
What Makes This Technology Special
Confusion Matrix
Visualize correct and incorrect predictions per class
Precision & Recall
Measure accuracy and coverage of the model
mAP (Mean Average Precision)
Standard metric for object detection models
PR Curve
Graph showing precision-recall trade-off
Cross-Validation
Test models on multiple data splits for reliability
A/B Testing
Compare old vs new models in real-world conditions
Benefits
Why You Need This Technology
Data-Driven Decisions
Choose the best model with data, not intuition
Reduce False Alarms
Tune thresholds to match business requirements
Track Degradation
Detect when models start performing worse (model drift)
Client Reports
Generate systematic model performance reports for clients
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