Per-paradigm accuracy tables
Precision, recall, and mAP50 for each detection model evaluated on each of the 24 paradigms. Reported with confidence intervals.
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← Capabilities
Model Benchmarking
Detection and pose accuracy validated across 24 behavioral paradigms
ConductVision publishes per-paradigm precision, recall, and mAP scores — not just overall accuracy numbers, but results specific to your experimental setup.
24
Paradigms benchmarked
20+
YOLO models evaluated
96.5%
Median detection recall
0.95+
Mean mAP50 score
The problem
Accuracy claims without paradigm-specific validation
Most tracking software reports a single accuracy number for "rodent tracking" without specifying which paradigm, lighting, arena, or camera angle was tested. A system validated on open field may fail on water maze or social interaction.
- Overall accuracy numbers hide paradigm-specific weaknesses
- No published validation data for reviewers to evaluate
- Difficult to assess suitability for your specific experimental setup
The solution
Published benchmarks for every supported paradigm
ConductVision evaluates 20+ detection models per paradigm and publishes precision, recall, mAP50, and fitness metrics — the same validation data you would include in a methods section.
- Per-paradigm accuracy tables available before purchase
- Precision, recall, and mAP50 reported per model per test
- Reviewer-ready documentation for your methods section
Endpoints
Benchmark results are published as structured data for reproducibility.
Model fitness metrics
Composite fitness score combining precision, recall, and mAP across evaluation sets. Guides model selection for your paradigm.
CSV
Cross-validation results
k-fold cross-validation performance to assess generalization. Separate train/test splits ensure benchmarks reflect real-world performance.
CSVJSON
Applications
Published benchmarks serve multiple roles in the research workflow.
Reviewer-ready accuracy reporting
Include published mAP and recall scores directly in your methods section. Reviewers can evaluate tracking quality without additional validation experiments.
Measures
- mAP50
- Precision
- Recall
Choose the best model for your paradigm
Compare detection performance across 20+ models evaluated on your specific test type. Select the model with the best accuracy-speed tradeoff for your setup.
Measures
- Fitness score
- Inference speed
- Accuracy
Data for equipment justification sections
Use published benchmark data to support ConductVision in equipment justification sections of R01, R21, and other NIH mechanisms.
Measures
- Published accuracy
- Paradigm coverage
- Cost comparison
Validate tracking quality per experiment
Compare your experiment detection metrics against published benchmarks to verify tracking quality before proceeding to analysis.
Measures
- Detection rate
- False positive rate
- Confidence threshold
Compared to typical systems
How ConductVision differs
| Feature | ConductVision | Typical systems |
|---|---|---|
| Published benchmarks | Per-paradigm, 24 tests | Single overall number |
| Models evaluated | 20+ per paradigm | 1 proprietary model |
| Metrics reported | Precision, recall, mAP50 | Accuracy percentage only |
| Cross-validation | k-fold results published | Not reported |
| Reviewer accessibility | Data tables available pre-purchase | Requires license to evaluate |
Related capabilities
Comparative Analysis
Side-by-side feature and performance comparison with EthoVision, ANY-maze, and other tracking platforms.
Custom Model Training
Train and validate custom behavior classifiers on lab-specific annotated data.
Precision Tracking
High-resolution 30 fps tracking that captures sub-second behavioral events conventional systems miss.
Review the benchmarks for your paradigm
Browse per-paradigm accuracy data before downloading — no license required to evaluate.
