Projects per year
Personal profile
Research interests
Pattern recognition, computer vision and machine vision, artificial neural networks, machine learning and deep learning. Applications in signal classification, medical image analysis, malware detection, industrial inspection.
Research engagement
Len engages with industry in R&D for a variety applications of machine vision and machine learning. He is currently the Principal Investigator on a project entitled Automatic Ship Classification Using Machine Learning. Past projects include:
- Recognition of targets in sonar images from autonomous underwater vehicles, with Defence Industry Network.
- Recognition of radar signals with Defence Services Technology Group.
- Locomotive pantograph inspection system (PanCam) with Aurizon Ltd. The developed system has been deployed since 2007 for timely automated detection and reporting of pantograph damage and wear.
- Biscuit bake inspection system with Arnott's Biscuits Ltd. Combines colour-calibrated image analysis with machine learning to report bake colour quality.
- Inspection of recycled glass colour purity with Visy Recycling.
Research student supervision
Len supervises PhD and MRes candidates in topics related to machine learning and image analysis. He is currently supervising one MRes candidate.
Recent completions:
Ava Assadi Abolvardi, "Deep learning-based Multiple-Sclerosis 3D lesions segmentation using small data," PhD, 2022.
Maryam Shahpasand, "Adversarial machine learning for enhanced malware detection," PhD, 2022.
Sonit Singh, "Multimodel machine learning for medical imaging," PhD, 2022.
Mahmood Yousefi-Azar, “Machine learning for automatic malware representation and analysis,” PhD, 2020.
Tahereh Hassanzadeh, "Convolutional neural networks for prostate magnetic resonance image segmentation," MRes, 2018.
Robert Newport, “Radar emitter recognition using hierarchical feature extraction within magnitude and frequency domains,” MRes, 2018.
Saruar Alam, “Impact of MRI technology on Alzheimer's disease detection,” MRes, 2018.
Mahmood Yousefi-Azar, “Query-oriented single-document summarization using unsupervised deep learning,” MRes, 2016.
Teaching
Len has over 30 years experience in University teaching, ranging across areas of computer science including networks and operating systems, computer architecture, computer graphics, and programming.
Len's innovative approach to teaching involves gamification and physical modeling of difficult concepts that arise in particular subject areas such as security protocols and 3D image formation. His innovations in assessment tasks include uniquely defining the task for each student and providing immediate evaluation and feedback throughout the task.
Education/Academic qualification
Computer Science, PhD, Computer Perception of Repetitive Textures, Carnegie Mellon University
Award Date: 26 Feb 1988
Statistics, BSc(hons), Macquarie University
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Collaborations and top research areas from the last five years
Projects
- 4 Finished
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AI-enabled Identity Verification
Beheshti, A., Hamey, L., Jolfaei, A. & Asadnia, M.
4/06/20 → 3/06/22
Project: Research
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Multimodal Machine Learning for Clinical Decision Support
Hamey, L. & Singh, S.
1/01/19 → 1/01/21
Project: Research
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Extending the Apply image processing language with application to OpenCV.
29/01/13 → 28/07/13
Project: Research
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Automated pathogen detection using time-gated luminescence microscopy
Connally, R., Piper, J., Shen, J., Iredell, J., Hamey, L. & APAI, A.
1/01/07 → 31/12/11
Project: Research
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Classification of ISAR ship imagery using transfer learning
Rosenberg, L., Zhao, W., Heng, A., Hamey, L., Nguyen, S. T. & Orgun, M. A., Feb 2024, In: IEEE Transactions on Aerospace and Electronic Systems. 60, 1, p. 25-36 12 p.Research output: Contribution to journal › Article › peer-review
5 Citations (Scopus) -
Hierarchical classification of ISAR sequences
Rosenberg, L., Zhao, W., Heng, A., Nguyen, S. T., Hamey, L. & Orgun, M., 2023, 2023 IEEE International Radar Conference (RADAR). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
1 Citation (Scopus) -
ISAR ship classification using transfer learning
Zhao, W., Heng, A., Rosenberg, L., Nguyen, S. T., Hamey, L. & Orgun, M., 2022, 2022 IEEE Radar Conference (RadarConf22) proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
14 Citations (Scopus) -
Mutual information and feature importance gradient boosting: automatic byte n-gram feature reranking for Android malware detection
Yousefi-Azar, M., Varadharajan, V., Hamey, L. & Chen, S., Jul 2021, In: Software: Practice and Experience. 51, 7, p. 1518-1539 22 p.Research output: Contribution to journal › Article › peer-review
5 Citations (Scopus) -
Show, tell and summarise: learning to generate and summarise radiology findings from medical images
Singh, S., Karimi, S., Ho-Shon, K. & Hamey, L., Jul 2021, In: Neural Computing and Applications. 33, 13, p. 7441-7465 25 p.Research output: Contribution to journal › Article › peer-review
16 Citations (Scopus)