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Qiang Fang
Qiang Fang
Research fellow; University of Toronto ;Université Laval,
Verified email at ulaval.ca - Homepage
Title
Cited by
Cited by
Year
Automated defect classification in infrared thermography based on a neural network
Y Duan, S Liu, C Hu, J Hu, H Zhang, Y Yan, N Tao, C Zhang, X Maldague, ...
NDT & E International 107, 102147, 2019
682019
A method of defect depth estimation for simulated infrared thermography data with deep learning
Q Fang, X Maldague
Applied Sciences 10 (19), 6819, 2020
422020
Automatic defects segmentation and identification by deep learning algorithm with pulsed thermography: Synthetic and experimental data
Q Fang, C Ibarra-Castanedo, X Maldague
Big Data and Cognitive Computing 5 (1), 9, 2021
412021
Automatic defect detection in infrared thermography by deep learning algorithm
Q Fang, BD Nguyen, CI Castanedo, Y Duan, X Maldague II
Thermosense: Thermal Infrared Applications XLII 11409, 180-195, 2020
312020
Introduction of the combination of thermal fundamentals and Deep Learning for the automatic thermographic inspection of thermal bridges and water-related problems in …
I Garrido, S Lagüela, Q Fang, P Arias
Quantitative InfraRed Thermography Journal 20 (5), 231-255, 2023
192023
Automated defect detection in non-planar objects using deep learning algorithms
Y Tao, C Hu, H Zhang, A Osman, C Ibarra-Castanedo, Q Fang, S Sfarra, ...
Journal of Nondestructive Evaluation 41 (1), 14, 2022
142022
Defect enhancement and image noise reduction analysis using partial least square-generative adversarial networks (PLS-GANs) in thermographic nondestructive evaluation
Q Fang, C Ibarra‐Castanedo, D Yuxia, J Erazo-Aux, I Garrido, ...
Journal of Nondestructive Evaluation 40, 1-26, 2021
82021
Automatic detection and identification of defects by deep learning algorithms from pulsed thermography data
Q Fang, C Ibarra-Castanedo, I Garrido, Y Duan, X Maldague
Sensors 23 (9), 4444, 2023
62023
University Laval Infrared Thermography Databases for Deep Learning Multiple Types of Defect Detections Training
Q Fang, C Ibarra-Castanedo, X Maldgue
Engineering Proceedings 2 (1), 32, 2021
52021
A reliability study on automated defect assessment in optical pulsed thermography
S Xiang, AM Omer, M Li, D Yang, A Osman, B Han, Z Gao, H Hu, ...
Infrared Physics & Technology 134, 104878, 2023
22023
Combination of thermal fundamentals and Deep Learning for infrastructure inspections from thermographic images. Preliminary results
I Garrido, S Lagüela, Q Fang, P Arias
Proceedings of the 15th Quantitative InfraRed Thermography, Porto, Portugal …, 2020
22020
Defect depth estimation in infrared thermography with deep learning
Q Fang, X Maldague
Preprints, 2021
12021
A novel approach for one-step defect detection and depth estimation using sequenced thermal signal encoding
W Zheng, S Zhang, AM Omer, Z Wu, N Tao, C Zhang, D Yang, H Zhang, ...
Nondestructive Testing and Evaluation, 1-16, 2024
2024
Defect Depth Estimation in Infrared Thermography with Deep Learning
Q Fang
https://www.preprints.org/manuscript/202008.0565/v1, 2020
2020
Combination of thermal fundamentals and Deep Learning for infrastructure inspections from thermographic images. Preliminary results
I Garrido González, S Lagüela López, Q Fang, P Arias Sánchez
15th Quantitative InfraRed Thermography, Oporto, Portugal, 6-10 julio 2020, 2020
2020
Height detection in smart baby weighing system using machine vision
Q Fang, H Tang
Automotive, Mechanical and Electrical Engineering, 371-374, 2017
2017
Automatic Crack Segmentation in Ancient Murals Using Optical Pulsed Thermography
J Cui, AM Omer, N Tao, C Zhang, Q Zhang, Y Ma, Z Zhang, D Yang, ...
Available at SSRN 4444961, 0
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