Abtin Djavadifar
Abtin Djavadifar
Master of Applied Science, University of British Columbia
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Cited by
Cited by
Object recognition datasets and challenges: A review
A Salari, A Djavadifar, X Liu, H Najjaran
Neurocomputing 495, 129-152, 2022
Automated visual detection of geometrical defects in composite manufacturing processes using deep convolutional neural networks
A Djavadifar, JB Graham-Knight, M Kӧrber, P Lasserre, H Najjaran
Journal of Intelligent Manufacturing 33 (8), 2257-2275, 2022
Segmentation of COVID-19 pneumonia lesions: A deep learning approach
Z Ghomi, R Mirshahi, AK Bagheri, A Fattahpour, S Mohammadiun, ...
Med J Islam Repub Iran 2020 (22), 174, 2020
Wrinkle and boundary detection of fiber products in robotic composites manufacturing
K Gupta, M Körber, A Djavadifar, F Krebs, H Najjaran
Assembly Automation 40 (2), 283-291, 2020
Robot-assisted composite manufacturing based on machine learning applied to multi-view computer vision
A Djavadifar, JB Graham-Knight, K Gupta, M Körber, P Lasserre, ...
Smart Multimedia: Second International Conference, ICSM 2019, San Diego, CA …, 2020
Accurate kidney segmentation in CT scans using deep transfer learning
JB Graham-Knight, K Scotland, VKF Wong, A Djavadifar, D Lange, ...
Smart Multimedia: Second International Conference, ICSM 2019, San Diego, CA …, 2020
Applying nnU-Net to the KiTS19 Grand Challenge
JB Graham-Knight, A Djavadifar, P Lasserre, H Najjaran
University of Minnesota Libraries Publishing, 2019
Boosted dense segmentation networks for constrained distributed systems
JB Graham-Knight, A Djavadifar, H Najjaran, P Lasserre
2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2021
Automatic detection of geometrical anomalies in composites manufacturing: a deep learning-based computer vision approach
A Djavadifar
University of British Columbia, 2020
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