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허석재 ( Heo¸ Seokjae ),이상현 ( Lee¸ Sanghyun ),이성원 ( Lee¸ Seungwon ),김명훈 ( Kim¸ Myunghun ),정란 ( Chung¸ Lan ) 한국건축시공학회 2021 한국건축시공학회 학술발표대회 논문집 Vol.21 No.2
The process before the model learning stage in AI R&D can be subdivided into data collection/cleansing-data purification-data labeling. After that, according to the purpose of development, it goes through a stage of verifying the model by performing learning by using the algorithm of the artificial intelligence model. Several studies describe an important part of AI research as the learning stage, and try to increase the accuracy by changing the structure and layer of the AI model. However, if the refinement and labeling process of the learning data is tailored only to the model format and is not made for the purpose of development, the desired AI model cannot be obtained. The latest research reveals that most AI research failures are the failure of the learning data rather than the structure of the AI model. analyzed.