Yanming Zhu

Senior Research Associate

Dr Yanming Zhu is a Research Associate in the School of Computer Science and Engineering. She received a B.E. degree from Shandong Agricultural University, China; a M.E. degree from Tianjin University, China; and a PhD degree in Computer Science from the University of New South Wales, Australia in 2019. 

Her research area is in Computer Vision, Deep Learning, Biomedical Image Analysis, and Biometrics. Her current research mainly focuses on the development of deep learning algorithms for cell segmentation and tracking.

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Journal articles
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Yin X; Zhu Y; Hu J, 2021, '3D Fingerprint Recognition based on Ridge-Valley-Guided 3D Reconstruction and 3D Topology Polymer Feature Extraction', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, pp. 1085 - 1091, http://dx.doi.org/10.1109/TPAMI.2019.2949299
2021
Yin X; Zhu Y; Hu J, 2020, 'Contactless Fingerprint Recognition Based on Global Minutia Topology and Loose Genetic Algorithm', IEEE Transactions on Information Forensics and Security, vol. 15, pp. 28 - 41, http://dx.doi.org/10.1109/TIFS.2019.2918083
2020
Li K; Zhu Y; Yang J; Jiang J, 2016, 'Video super-resolution using an adaptive superpixel-guided auto-regressive model', Pattern Recognition, vol. 51, pp. 59 - 71, http://dx.doi.org/10.1016/j.patcog.2015.08.008
2016
Zhu Y; Li K; Jiang J, 2014, 'Video super-resolution based on automatic key-frame selection and feature-guided variational optical flow', Signal Processing: Image Communication, vol. 29, pp. 875 - 886, http://dx.doi.org/10.1016/j.image.2014.06.005
2014
Book Chapters
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Yin X; Zhu Y, 2021, '3D Fingerprint', in Encyclopedia of Cryptography, Security and Privacy, Springer, Berlin, Heidelberg, http://dx.doi.org/10.1007/978-3-642-27739-9_1513-1
2021
Conference Papers
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Zhu Y; Meijering E, 2020, 'Neural Architecture Search for Microscopy Cell Segmentation', Lima, Peru, presented at Neural Architecture Search for Microscopy Cell Segmentation, Lima, Peru, 04 October 2020
2020
Zhu Y; Yin X; Jia X; Hu J, 2017, 'Latent Fingerprint Segmentation Based on Convolutional Neural Networks', in 2017 IEEE Workshop on Information Forensics and Security (WIFS), Rennes, France, pp. 1 - 6, presented at 2017 IEEE Workshop on Information Forensics and Security (WIFS), Rennes, France, 04 December 2017 - 07 December 2017, http://dx.doi.org/10.1109/WIFS.2017.8267655
2017
Yin X; Zhu Y; Hu J, 2017, 'A robust contactless fingerprint enhancement algorithm', in Hu J; Khalil I; Tari Z; Wen S (eds.), Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer, Melbourne, Australia, pp. 127 - 136, presented at 9th International Conference, MONAMI 2017, Melbourne, Australia, 13 December 2017 - 15 December 2017, http://dx.doi.org/10.1007/978-3-319-90775-8_11
2017
Zhu Y; Yin X; Hu J, 2017, 'Robust fingerprint matching based on convolutional neural networks', in Hu J; Khalil I; Tari Z; Wen S (eds.), Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer, Melbourne, Australia, pp. 56 - 65, presented at 9th International Conference, MONAMI 2017, Melbourne, Australia, 13 December 2017 - 15 December 2017, http://dx.doi.org/10.1007/978-3-319-90775-8_5
2017
Zhu Y; Hu J; Xu J, 2016, 'A robust multi-constrained model for fingerprint orientation field construction', in Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016, China, pp. 156 - 160, presented at 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA), China, 05 June 2016 - 07 June 2016, http://dx.doi.org/10.1109/ICIEA.2016.7603569
2016
Zhu Y; Li K; Jiang J; Yang J, 2013, 'Adaptive video super-resolution based on superpixel-guided auto-regressive model', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 453 - 464, http://dx.doi.org/10.1007/978-3-319-03731-8_42
2013
Zhu Y; Jiang J; Li K, 2012, 'Optimized image super-resolution based on sparse representation', in Proceedings - International Conference on Pattern Recognition, pp. 1052 - 1055
2012