Inference using custom calssifer and fine-tuned feature extractor to identify defects on patches/tiles of dynamically processed video frames in challenging (for AI) enviroments:
State of the art deep learning anomaly detection methods augmented with traditional computer vision to detect defects on the borders and in the critical region with (close to) pixel perfect acccuracy:
Code
Classification of metal diaphragms and their visual explanations using Grad-CAM and RISE:
Code Paper
Diameter detection of the hole in adapters accurately to the tenth of a millimeter using a Raspberry Pi and a Pi camera:
Detection of gel and lids using histogram matching along with contour area and shape-based constraints:
Published in Proc. Korea Information and Communications Society (KICS) Summer Conference, 2020
Recommended citation: S. M. Kazim, A. Farooq, J. ur Rehman, and H. Shin, "Applied Bayesian Qubit State Tomography," Proc. Korea Information and Communications Society (KICS) Summer Conference, pp. 190-192 Korea, Aug. 2020.
Published in Proc. Korea Information and Communications Society (KICS) Winter Conference, 2021
Recommended citation: S. M. Kazim, J. ur Rehman, and H. Shin, "Adaptive Optimal Basis Tomography for Qubits," Proc. Korea Information and Communications Society (KICS) Winter Conference, pp. 395-396 Korea, Feb. 2021.
Published in Quantum Inf. Process., 2021
Recommended citation: S. M. Kazim, A. Farooq, J. ur Rehman, and H. Shin, "Adaptive quantum state tomography with iterative particle filtering," Quantum Inf. Process., Sep. 2021 https://link.springer.com/article/10.1007/s11128-021-03267-x
Published in Proc. Korea Information and Communications Society (KICS) Winter Conference, 2022
Recommended citation: S. M. Kazim, J. ur Rehman, and H. Shin, "Robust Ground State Tomography with Neural Networks," Proc. Korea Information and Communications Society (KICS) Winter Conference, Feb. 2022
Published in , 2022
Recommended citation: S. M. Kazim, J. Tayyub, M. Sarmad, and Patrick Werner, "Metal Diaphragm Seal Defect Detection Using Convolutional Neural Networks," Feb. 2022
Published:
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Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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