Dr. Tongguang Ni Profile

Dr. Tongguang Ni

Professor at Changzhou Univ

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Author

Publications (4)

SPIE Journal Paper | 11 August 2018 Open Access

Person reidentification by semisupervised dictionary rectification learning with retraining module

Hongyuan Wang, Zongyuan Ding, Ji Zhang, Suolan Liu, Tongguang Ni, Fuhua Chen

JEI, Vol. 27, Issue 04, 043043, (August 2018) https://doi.org/10.1117/12.10.1117/1.JEI.27.4.043043

KEYWORDS: Associative arrays, Machine learning, Data modeling, Statistical modeling, Intelligence systems, Performance modeling, Visual process modeling, RGB color model, Nickel, Facial recognition systems

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SPIE Journal Paper | 27 July 2018 Open Access

Discriminative deep transfer metric learning for cross-scenario person re-identification

Tongguang Ni, Xiaoqing Gu, Hongyuan Wang, Zhongbao Zhang, Shoubing Chen, Cui Jin

JEI, Vol. 27, Issue 04, 043026, (July 2018) https://doi.org/10.1117/12.10.1117/1.JEI.27.4.043026

KEYWORDS: Data modeling, Neural networks, Cameras, Distance measurement, Nickel, Statistical analysis, Surveillance systems, Principal component analysis, Detection and tracking algorithms, Machine vision

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Proceedings Article | 14 May 2018 Paper

Person re-identification by semi-supervised dictionary rectification learning

Zongyuan Ding, Hongyuan Wang, Fuhua Chen, Suolan Liu, Tongguang Ni

Proceedings Volume 10670, 106700M (2018) https://doi.org/10.1117/12.2309840

KEYWORDS: Associative arrays, Machine learning, Intelligence systems, Data modeling, RGB color model, Evolutionary algorithms, Statistical modeling, Facial recognition systems, Cameras, Performance modeling

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Proceedings Article | 14 May 2018 Paper

Discriminative deep transfer metric learning for cross-scenario person re-identification

Tongguang Ni, Zhongbao Zhang, Hongyuan Wang, Shoubing Chen, Cui Jin

Proceedings Volume 10670, 106700P (2018) https://doi.org/10.1117/12.2309854

KEYWORDS: Data modeling, Cameras, Distance measurement, Neural networks, Surveillance systems, Visualization, Machine vision, Computer vision technology, Feature extraction, Mahalanobis distance

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