Software

Artificial Intelligence for the Computer-Aided Detection of Periapical Lesions in Cone-Beam Computed Tomographic Images
Introduction The aim of this study was to use a Deep Learning (DL) algorithm for the automated segmentation of cone-beam computed …
Frank C. Setzer, Katherine J. Shi, Zhiyang Zhang, Hao Yan, Hyunsoo Yoon, Mel Mupparapu, Jing Li
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Data-driven trajectory prediction with weather uncertainties: A Bayesian deep learning approach
Trajectory prediction is an essential component of the next generation national air transportation system. Reliable trajectory …
Yutian Pang, Xinyu Zhao, Hao Yan, Yongming Liu
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Combining Anatomical Constraints and Deep Learning for 3-D CBCT Dental Image Multi-Label Segmentation
Machine learning research on medical images is becoming popular as advanced imaging technologies and equipment in medicine become more …
Jiayu Huang, Hao Yan, Jing Li, H. Milton Stewart, Frank Setzer
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Image Decomposition-Based Sparse Extreme Pixel-Level Feature Detection Model with Application to Medical Images
Pixel-level feature detection from images is an essential but challenging task encountered in domains such as detecting defects in …
Geet Lahoti, Jialei Chen, Xiaowei Yue, Hao Yan, Chitta Ranjan, Zhen Qian, Chuck Zhang, Ben Wang
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Adaptive Change Point Monitoring for High-Dimensional Data
In this paper, we propose a class of monitoring statistics for a mean shift in a sequence of high-dimensional observations. Inspired by …
Teng Wu, Runmin Wang, Hao Yan, Xiaofeng Shao
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Deep Multistage Multi-Task Learning for Quality Prediction and Diagnostics of Multistage Manufacturing Systems
In multistage manufacturing systems, modeling multiple quality indices based on the process sensing variables is important. However, …
Hao Yan, Nurretin D. Sergin, William A. Brenneman, Stephen J. Lange, Shan Ba
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Deep Multistage Multi-Task Learning for Quality Prediction and Diagnostics of Multistage Manufacturing Systems
Edge Computing Accelerated Defect Classification Based on Deep Convolutional Neural Network With Application in Rolling Image Inspection
This paper develops a unified framework for training and deploying deep neural networks on the edge computing framework for image …
Jiayu Huang, Nurretin Sergin, Akshay Dua, Erfan Bank Tavakoli, Hao Yan, Fengbo Ren, Feng Ju
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Hierarchical Tree-Based Sequential Event Prediction with Application in the Aviation Accident Report
Sequential event prediction is a well-studied area and has been widely used in proactive management, recommender systems and …
Xinyu Zhao, Hao Yan, Yongming Liu
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Hierarchical Tree-Based Sequential Event Prediction with Application in the Aviation Accident Report
Real-Time Detection of Clustered Events in Video-Imaging Data with Applications to Additive Manufacturing
The use of video-imaging data for in-line process monitoring applications has become more and more popular in the industry. In this …
Hao Yan, Marco Grasso, Kamran Paynabar, Bianca Maria Colosimo
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Toward a Better Monitoring Statistic for Profile Monitoring via Variational Autoencoders
Variational autoencoders have been recently proposed for the problem of process monitoring. While these works show impressive results …
Nurettin Dorukhan Sergin, Hao Yan
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Toward a Better Monitoring Statistic for Profile Monitoring via Variational Autoencoders