Home > Staffs 2025 > 01 Team members > ZHOU Yanghong
Dr. ZHOU Yanghong
Deputy Team Leader, Research Assistant Professor at PolyU
staff description
Business development for computer aided fashion intelligence and marketing/design for computer aided fashion intelligence
- Participated Projects
It seems we can’t find what you’re looking for.
- Participated Publications
A Part-Based Deep Neural Network Cascade Model for Human Parsing
Zhou, Y., Mok, P. Y.*, and Zhou, S. (2019) A Part-Based Deep Neural Network Cascade Model for Human Parsing. IEEE Access, (Journal Impact Factor 3.9, Q2 73/158 in the category of ‘computer science, information systems’), 7, 160101-160111.
- 2019
Deep Learning Fine-grainedClothingattributes in unconstrained image
Zhou Y.H. and Mok, P. Y.*, Deep Learning Fine-grainedClothingattributes in unconstrained image, The 14th Asian Textile Conference, 28-30 Jun 2017, Hong Kong.
- 2017
Fashion recommendations using text mining and multiple content attributes
Zhou Wei, Zhou Yanghong, Runze Li, and .Y. Mok*, Fashion recommendations using text mining and multiple content attributes, The 25th International Conference on Computer Graphics, Visualization and Computer Vision 2017 (WSCG2017), May 29 – June 2017, Plzen, Czech Republic.
- 2017
Human parsing with Convolutional Neural Network
Y.H. Zhou and Mok, P. Y.*, Human parsing with Convolutional Neural Network, Textile Summit 2016 and Postgraduate Student Conference, 28-30 June 2016, Hong Kong.
- 2016
A part-detection based and CRFs embedded deep neural network for human parsing
Zhou Y.H. and Mok, P. Y.*, A part-detection based and CRFs embedded deep neural network for human parsing, Proceedings of the third International Conference and Expo on Computer Graphics & Animation, 07-09 Nov 2016, Las Vegas, USA.
- 2016
Web-based Fashion Sketch Design System for Skirts
Jie Xu, Yanghong Zhou, Mok, P. Y.*, R.W.Y. Yee, C.W. Yuen, Web-based Fashion Sketch Design System for Skirts, Proceedings of The fifth Cross-straits Conference on Textiles, 17-19 Dec, 2014, Hong Kong, pp. 468-473.
- 2014