Dataset Groups Activity Stream ARS: Augmented Reality Semi-automatic-labeling Two novel datasets are created using the ARS pipeline, one on electromechanical components (industrial scenario) and one on fruits (daily-living scenario). BibTex: @dataset{Daniele_De_Gregorio_and_Alessio_Tonioni_and_Gianluca_Palli_and_Luigi_Di_Stefano_2024, abstract = {Two novel datasets are created using the ARS pipeline, one on electromechanical components (industrial scenario) and one on fruits (daily-living scenario).}, author = {Daniele De Gregorio and Alessio Tonioni and Gianluca Palli and Luigi Di Stefano}, doi = {10.57702/uphhqvad}, institution = {No Organization}, keyword = {'ARS', 'Deep learning', 'Object detection', 'Semi-automatic labeling'}, month = {dec}, publisher = {TIB}, title = {ARS: Augmented Reality Semi-automatic-labeling}, url = {https://service.tib.eu/ldmservice/dataset/ars--augmented-reality-semi-automatic-labeling}, year = {2024} }
