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In the proposed study, we describe the possibility of automated datasetcollection using an articulated robot. The proposed technology reduces thenumber of pixel errors on a polygonal dataset and the time spent on manuallabeling of 2D objects. The paper describes a novel automatic datasetcollection and annotation system, and compares the results of automated andmanual dataset labeling. Our approach increases the speed of data labeling240-fold, and improves the accuracy compared to manual labeling 13-fold. Wealso present a comparison of metrics for training a neural network on amanually annotated and an automatically collected dataset.

DeepScanner: a Robotic System for Automated 2D Object Dataset Collection with Annotations