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Publication date Communities Collections Article title Author(s) Journal/Conference
21 Jun 2022 SERC Institute for Infocomm Research Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition Mei Chee Leong, Haosong Zhang, Hui Li Tan, Liyuan Li, Joo Hwee Lim The Ninth Workshop on Fine-Grained Visual Categorization
1 Oct 2020 SERC Institute for Infocomm Research Improving 3D Brain Tumor Segmentation With Predict-Refine Mechanism Using Saliency And Feature Maps Ramanpreet Singh Pahwa, Tin Lay Nwe, Oo Zaw Min, Gopalakrishnan Saisubramaniam, Lin Dongyun, Prasad Shitala, Li Yiqun, Dong Sheng IEEE International Conference on Image Processing (ICIP)
1 May 2020 SERC Institute for Infocomm Research Citywide Traffic Flow Prediction Based on Multiple Gated Spatio-temporal Convolutional Neural Networks Cen Chen, Kenli Li, Sin G. Teo, Xiaofeng Zou, Keqin Li, Zeng Zeng ACM Transactions on Knowledge Discovery from Data
31 Jan 2020 SERC Institute for Infocomm Research DCE-MRI pharmacokinetic parameter maps for cervical carcinoma prediction Jianbo Shao, Zhuo Zhang, Huiying Liu, Ying Song, Zhihan Yan, Xue Wang, Zuju Hou Computers in Biology and Medicine
10 Dec 2019 SERC Institute for Infocomm Research Convolutional Neural Networks for Absence Seizure Detection with Frontal EEG Electrodes Zhuo Zhang, Dajiang He, Mustafa Talha Avcu, Derrick Wei Shih Chan The 17th International Conference on Biomedical Engineering (ICBME)
20 Nov 2018 SERC Institute for Infocomm Research Exploiting Spatio-Temporal Correlations with Multiple 3D Convolutional Neural Networks for Citywide Vehicle Flow Prediction Cen Chen, Kenli Li, Sin G. Teo, Guizi Chen, Xiaofeng Zou, Xulei Yang, Ramaseshan C. Vijay, Jiashi Feng, Zeng Zeng IEEE International Conference on Data Mining
6 Nov 2018 SERC Institute of High Performance Computing Traffic Speed Prediction with Convolutional Neural Network Adapted for Non-linear Spatio-temporal Dynamics Shen Ren, Bo Yang, Liye Zhang, Zengxiang Li Proceedings of the 7th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data