Big Massive Open Online Course (MOOC) Data Retrieval and Classification Based on Cognitive Style

Project Member(s): Li, J.

Funding or Partner Organisation: Guangdong Polytechnic Normal University
Guangdong Polytechnic Normal University

Start year: 2017

Publications:

Zhang, Y, Lv, P, Lu, X & Li, J 2019, 'Face detection and alignment method for driver on highroad based on improved multi-task cascaded convolutional networks', Multimedia Tools and Applications, vol. 78, no. 18, pp. 26661-26679.
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Li, J, Chen, Z & Ma, Z 2018, 'Learning Colours from Textures by Effective Representation of Images' in Yurish, SY (ed), Advances in Signal Processing: Reviews, International Frequency Sensor Association (IFSA) Publishing, Spain, pp. 277-304.

Kang, G, Li, J & Tao, D 2018, 'Shakeout: A New Approach to Regularized Deep Neural Network Training', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, pp. 1245-1258.
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Li, J, Mei, X, Prokhorov, D & Tao, D 2017, 'Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene', IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 3, pp. 690-703.
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Chen, Z, Li, J, Chen, Z & You, X 1970, 'Generic Pixel Level Object Tracker Using Bi-Channel Fully Convolutional Network', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Neural Information Processing, Springer International Publishing, Guangzhou, China, pp. 666-676.
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Chen, Z, You, X & Li, J 1970, 'Learning to focus for object proposals', 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), IEEE, Shenzhen, China, pp. 439-444.
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FOR Codes: Artificial Intelligence and Image Processing, Education and Training Systems Policies and Development, Information and Communication Services, Information retrieval and web search, Policies and development

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.