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Max Ferguson
Max Ferguson
在 stanford.edu 的电子邮件经过验证
标题
引用次数
引用次数
年份
Automatic Localization of Casting Defects with Convolutional Neural Networks
M Ferguson, R Ak, YTT Lee, KH Law
2017 IEEE International Conference on Big Data, 2017
2522017
Detection and segmentation of manufacturing defects with convolutional neural networks and transfer learning
MK Ferguson, AK Ronay, YTT Lee, KH Law
Smart and sustainable manufacturing systems 2, 2018
2442018
Sensor data reconstruction using bidirectional recurrent neural network with application to bridge monitoring
S Jeong, M Ferguson, R Hou, JP Lynch, H Sohn, KH Law
Advanced engineering informatics 42, 100991, 2019
932019
Segmentation of additive manufacturing defects using U-net
VWH Wong, M Ferguson, KH Law, YTT Lee, P Witherell
Journal of Computing and Information Science in Engineering 22 (3), 031005, 2022
53*2022
Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)
J Park, DJ Lechevalier, R Ak, MK Ferguson, KH Law, YTT Lee, S Rachuri, ...
The ASTM Journal of Smart and Sustainable Manufacturing 1 (1), 2017
412017
Sensor data reconstruction and anomaly detection using bidirectional recurrent neural network
S Jeong, M Ferguson, KH Law
Sensors and Smart Structures Technologies for Civil, Mechanical, and …, 2019
272019
Detection and segmentation of manufacturing defects with convolutional neural networks and transfer learning. Smart Sustain Manuf. Syst.(2018)
M Ferguson, A Ronay, YT Tina Lee, KH Law
202018
A 2d-3d object detection system for updating building information models with mobile robots
M Ferguson, K Law
2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 1357-1365, 2019
182019
R. ak, Y
M Ferguson
T. Lee, and K. Law,“Automatic localization of casting defects with …, 2017
162017
A Generalized Method for Featurization of Manufacturing Signals, with Application to Tool Condition Monitoring
M Ferguson, KH Law, R Bhinge, YTT Lee
112017
ak, Ronay & Lee, Yung-Tsun & Law, Kincho.(2017)
M Ferguson
Automatic localization of casting defects with convolutional neural networks …, 0
11
A standardized representation of convolutional neural networks for reliable deployment of machine learning models in the manufacturing industry
M Ferguson, S Jeong, KH Law, S Levitan, A Narayanan, R Burkhardt, ...
International Design Engineering Technical Conferences and Computers and …, 2019
92019
Worksite object characterization for automatically updating building information models
M Ferguson, S Jeong, KH Law
ASCE International Conference on Computing in Civil Engineering 2019, 303-311, 2019
92019
A data processing pipeline for prediction of milling machine tool condition from raw sensor data
M Ferguson, R Bhinge, J Park, YT Lee, KH Law
Smart and sustainable manufacturing systems 2, 2018
72018
Automatic localization of casting defects with convolutional neural networks
R Ak, M Ferguson, YTT Lee, KH Law
Ronay Ak, Max Ferguson, Yung-Tsun T. Lee, Kincho H. Law, 2017
72017
A data-driven approach for sensor data reconstruction for bridge monitoring
K Law, S Jeong, M Ferguson
2017 World Congress on Advances in Structural Engineering and Mechanics, 2017
72017
Evaluation of a PMML-based GPR scoring engine on a cloud platform and microcomputer board for smart manufacturing
M Ferguson, KH Law, R Bhinge, D Dornfeld, J Park, YTT Lee
2016 IEEE International Conference on Big Data (Big Data), 2014-2023, 2016
62016
An assistive learning workflow on annotating images for object detection
VWH Wong, M Ferguson, KH Law, YTT Lee
2019 IEEE International Conference on Big Data (Big Data), 1962-1970, 2019
52019
A standardized PMML format for representing convolutional neural networks with application to defect detection
M Ferguson, YTT Lee, A Narayanan, KH Law
Smart and sustainable manufacturing systems 3 (1), 79, 2019
52019
Data driven analytics (machine learning) for system characterization, diagnostics and control optimization
J Park, M Ferguson, KH Law
Advanced Computing Strategies for Engineering: 25th EG-ICE International …, 2018
52018
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