Lihong Zheng — Charles Sturt University Research Output

Personal profile

Currently Involved in research at Charles Sturt University.

Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

Gesture recognition Engineering & Materials Science

Support vector machines Engineering & Materials Science

Neural networks Engineering & Materials Science

Blood vessels Engineering & Materials Science

Medium access control Engineering & Materials Science

Time series Engineering & Materials Science

Classifiers Engineering & Materials Science

Vehicular ad hoc networks Engineering & Materials Science

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Research Output 2003 2019

245 Citations
9 h-Index
38 Conference paper
18 Article
9 Doctoral Thesis
1 Chapter

Deep Learning Models for Retinal Blood Vessels Segmentation: A Survey

Soomro, T. A., Zheng, L., Gao, J., Hellwich, O. & Paul, M., 23 May 2019, (Accepted/In press) In : IEEE Access.

Research output: Contribution to journal › Article

Sequential deep learning for action recognition with synthetic multi-view data from depth maps

Liang, B., Zheng, L. & Li, X., 2019, Data Mining - 16th Australasian Conference, AusDM 2018, Revised Selected Papers. Zhao, Y., Warwick, G., Stirling, D., Li, C-T., Koh, Y. S., Islam, R. & Islam, Z. (eds.). Springer-Verlag London Ltd., p. 360-371 12 p. (Communications in Computer and Information Science; vol. 996).

Research output: Book chapter/Published conference paper › Conference paper

Action Recognition

Depth Map

Recurrent neural networks

Neural networks

Motion

Strided Fully Convolutional Neural Network for Boosting the Sensitivity of Retinal Blood Vessels Segmentation

Soomro, T. A., Afifi, A. J., Gao, J., Hellwich, O., Zheng, L. & Paul, M., 22 May 2019, (Accepted/In press) In : Expert Systems with Applications. 17 p.

Research output: Contribution to journal › Article

Blood vessels

Neural networks

Principal component analysis

Processing

1 Citation (Scopus)

Strided U-Net Model: Retinal Vessels Segmentation using Dice Loss

Soomro, T. A., Hellwich, O., Afifi, A. J., Paul, M., Gao, J. & Zheng, L., 16 Jan 2019, 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018. Pickering, M., Zheng, L., You, S., Rahman, A., Murshed, M., Asikuzzaman, M., Natu, A., Robles-Kelly, A. & Paul, M. (eds.). IEEE, Institute of Electrical and Electronics Engineers, 8615770. (2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018).

Research output: Book chapter/Published conference paper › Conference paper

Retinal Vessels

Databases

Neural networks

Neural Networks (Computer)

Lighting