Development of Efficient Cloud Dataset Construction System with Machine Learning Scheme

Abstract

Machine learning attracts attention in environment recognitions. Annotations of an enormous dataset are mainly performed with many time and effort. Therefore, the system of an automatic annotation of the dataset is required. We propose the dataset construction system by the machine learning with a cloud server. In our approach, image collection is performed by multiple robots with a cloud server, and automatic annotation is done by machine learning. In addition, misrecognitions of the machine learning are corrected by hand, and classification re-learns the corrected results. Finally, we compared the required time, that dataset construction by our approach took, with that by previous methods.