Queue uncertain first
Wrong or inconsistent labels are not used for training. They move to a verification queue instead.
Interactive Demo
Active Learning Console
Human-in-the-loop annotation refinement
Top-K selection
0/2 batch
0 rounds
Open demo
Batch active learning console
Correct uncertain images. Train after a verified batch.
The model ranks informative charger images. Human labels are checked first; verified samples enter a review batch. Metrics improve only after the batch is large enough for the next training round.
SelectionTop-K
Batch0/2
Round0
Annotation classification
IMG-042low confidence + low similarity
Signals impact
Uncertainty0.82
AL value0.87
Verified batch0/2
Train round0
Model metricsBefore
Original baselineCurrent model
Verified sample added to batch.