Indoor object segmentation based on YOLACT++ Online publication date: Wed, 19-Apr-2023
by Ying Sun; Zichen Zhao; Bo Tao; Xin Liu; Juntong Yun; Ying Liu
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 24, No. 2, 2023
Abstract: Intelligent Manufacturing originates from the research of artificial intelligence, which can not only reduce operating costs, but also improve product quality, and has become the way to cultivate new advantages in forging international competition in manufacturing. With the transformation of traditional manufacturing to intelligent manufacturing, the course of intelligent manufacturing should also be different from the traditional teaching mode, but through the survey, it has been found that the course of intelligent manufacturing still has a single teaching mode, insufficient innovative guidance for students and insufficient combination of theory and practice. In order to solve the issues mentioned above, the Project-Analysis-Evaluation (PAE) structure is proposed in this paper, and it is combined with constructivist theory and analysed through the study of indoor object instance segmentation detection. The YOLACT++ algorithm is pre-trained on SUNRGBD dataset and applied to indoor environment detection in this paper.
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