BSc. in EEE | MEng. in Electronics | PhD in Computer Vision (Expected)
Researcher: Computer Vision | Machine Learning | Deep Learning
Deakin University | Geelong, VIC, Australia
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This comprehensive undergraduate project focused on the analysis and implementation of advanced power electronics systems with emphasis on power factor correction and converter efficiency optimization. The project addressed critical challenges in power quality, harmonic distortion reduction, and adaptive power management systems.
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This collaborative project involved the design and implementation of a comprehensive Traffic Light Controller (TLC) system using FPGA technology. The project required advanced digital design skills, finite state machine implementation, and practical hardware interfacing for real-world traffic management applications.
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This project involved the complete design and implementation of a 68HC11-compatible microcontroller using hardware description languages. The work required comprehensive understanding of processor architecture, digital system design, and FPGA implementation methodologies.
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This was a pioneering research project completed during my Master’s degree that developed an innovative wearable ultraviolet light-detecting system with wireless communication capabilities. This project addressed the critical health challenge of balancing beneficial UV exposure for vitamin D synthesis while preventing harmful overexposure that can lead to skin damage and cancer.
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This advanced RF circuit design project involved the complete development of a Low Noise Amplifier (LNA) system, from initial circuit design through final package implementation. The project addressed critical RF design challenges including noise optimization, impedance matching, and electromagnetic compatibility.
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This project focused on the comprehensive design and implementation of digital logic circuits using CMOS technology. The work involved developing both universal and compound gates while mastering the fundamental principles of CMOS logic design and transistor-level implementation.
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This project involved the design and development of advanced reconfigurable antenna systems capable of operating across multiple frequency bands. The work focused on implementing frequency-agile antenna solutions using electronic switching mechanisms for modern wireless communication applications.
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RF Technology is a leading Australian manufacturer of wireless communication products. My responsibilities included:
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EMVision is an innovative medical device company developing portable electromagnetic microwave imaging solutions. My responsibilities included:
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I worked as a sessional academic staff member at Deakin University, contributing to the Deep Learning (SIT319, SIT744) and Artificial and Computational Intelligence (SIT215) units. My responsibilities included conducting tutorials and workshops, as well as marking assignments. During the workshops, I:
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Published in Structural, Syntactic, and Statistical Pattern Recognition, 2022
This paper is about the multi-label image classification using a capsule network.
Recommended citation: K. T. Noor, A. Robles-Kelly, and B. Kusy, ‘A Capsule Network for Hierarchical Multi-label Image Classification’, in Structural, Syntactic, and Statistical Pattern Recognition, A. Krzyzak, C. Y. Suen, A. Torsello, and N. Nobile, Eds., in Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022, pp. 163–172. doi: 10.1007/978-3-031-23028-8_17.
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Published in 2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2023
This paper is about the hierarchical image classification using a bottom-up strategy.
Recommended citation: K. T. Noor, A. Robles-Kelly, L. Y. Zhang, and M. R. Bouadjenek, ‘A Bottom-Up Capsule Network for Hierarchical Image Classification’, in 2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Nov. 2023, pp. 325–331. doi: 10.1109/DICTA60407.2023.00052.
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Published in Pattern Recognition, 2024
This paper is about the hierarchical multi-label image classification using a capsule network.
Recommended citation: K. T. Noor and A. Robles-Kelly, ‘H-CapsNet: A capsule network for hierarchical image classification’, Pattern Recognition, vol. 147, p. 110135, Mar. 2024, doi: 10.1016/j.patcog.2023.110135.
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Published in Neurocomputing, 2024
This paper is about the consistency-aware hierarchical multi-label image classification using a deep capsule network.
Recommended citation: K. T. Noor, A. Robles-Kelly, L. Y. Zhang, M. R. Bouadjenek, and W. Luo, ‘A consistency-aware deep capsule network for hierarchical multi-label image classification’, Neurocomputing, vol. 604, p. 128376, Nov. 2024, doi: 10.1016/j.neucom.2024.128376.
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Published in Knowledge-Based Systems, 2025
This paper is about the consistency-aware hierarchical multi-label image classification using a deep capsule network.
Recommended citation: Noor, K. T., Luo, W., Robles-Kelly, A., Zhang, L. Y., & Bouadjenek, M. R. (2025). Taxonomy-Guided Routing in Capsule Network for Hierarchical Multi-Label Image Classification (SSRN Scholarly Paper No. 5127434). Social Science Research Network. https://doi.org/10.2139/ssrn.5127434
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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Workshop, University 1, Department, 2015
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