Active Learning with Multiple Annotators

Multi-source Label Aggregation

Fusion technique combining labels from multiple annotators into a single consensus prediction, using methods such as weighted voting, Dawid-Skene models, or Bayesian inference. This aggregation corrects individual errors and produces more reliable labels.

← Kembali