Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Engineering
Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli
Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
The role of human-machine teams in society is increasing, as big data and computing power explode. One popular approach to AI is deep learning, which is useful for classification, feature identification, and predictive modeling. However, deep learning models often suffer from inadequate transparency and poor explainability. One aspect of human systems integration is the design of interfaces that support human decision-making. AI models have multiple types of uncertainty embedded, which may be difficult for users to understand. Humans that use these tools need to understand how much they should trust the AI. This study evaluates one simple approach for communicating …
Real-Time Assembly Operation Recognition With Fog Computing And Transfer Learning For Human-Centered Intelligent Manufacturing, Wenjin Tao, Md Al-Amin, Haodong Chen, Ming-Chuan Leu, Zhaozheng Yin, Ruwen Qin
Real-Time Assembly Operation Recognition With Fog Computing And Transfer Learning For Human-Centered Intelligent Manufacturing, Wenjin Tao, Md Al-Amin, Haodong Chen, Ming-Chuan Leu, Zhaozheng Yin, Ruwen Qin
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In a human-centered intelligent manufacturing system, every element is to assist the operator in achieving the optimal operational performance. The primary task of developing such a human-centered system is to accurately understand human behavior. In this paper, we propose a fog computing framework for assembly operation recognition, which brings computing power close to the data source in order to achieve real-time recognition. For data collection, the operator's activity is captured using visual cameras from different perspectives. For operation recognition, instead of directly building and training a deep learning model from scratch, which needs a huge amount of data, transfer learning …