In the realm of machine learning and data annotation, model - assisted labeling is a process where human annotators utilize pre-trained machine learning models to aid in data labeling. Departing from the traditional approach of relying solely on manual annotation, which is often time-consuming and costly, this method capitalizes on the predictions of machine learning models to expedite the annotation workflow. It enables labeling teams to concentrate their time on fine-tuning, validating, or discarding the model predictions, rather than painstakingly creating each label from the very beginning.
Currently, mainstream platforms providing model-assisted labeling include Roboflow, Labelbox, Label Studio, T-Rex Label(https://www.trexlabel.com/?source=dds), and so on.