Accuracy Optimization Guide
The following calibration methods are recommended for possible errors in AI recognition:
- Data preparation phase::
- Ensure video resolution ≥ 1080p and good lighting conditions
- Creation of an annotated dictionary in advance for specialized terms/special items (e.g., names of medical devices)
- Model training phase::
- Upload misclassified samples for retraining using the platform's enterprise customization feature
- Set confidence threshold (recommended initial value of 85%)
- Results calibration phase::
- Enable "manual review mode" to validate key analysis nodes
- Utilizing multimodal cross-validation (e.g., matching screen elements and dialog content simultaneously)
advanced skill: Update the model periodically (quarterly is recommended) to maintain recognition sensitivity to emerging visual patterns. Appropriate tuning of these parameters can improve accuracy to 92%+.
This answer comes from the articleMemories.ai: an AI visual memory tool for analyzing video contentThe
May not be reproduced without permission:AI productivity tools " How to Avoid the Misclassification Problem in Video Analytics and Improve Memories.ai Recognition Accuracy?
