A series of NiM (M= Ru, Rh, and Pd) bimetallic catalysts for effective lignin hydrogenolysis in water J Zhang, J Teo, X Chen, H Asakura, T Tanaka, K Teramura, N Yan Acs Catalysis 4 (5), 1574-1583, 2014 | 478 | 2014 |
Exploring dynamic self-adaptive populations in differential evolution J Teo Soft computing 10, 673-686, 2006 | 455 | 2006 |
EEG-based emotion recognition: A state-of-the-art review of current trends and opportunities NS Suhaimi, J Mountstephens, J Teo Computational intelligence and neuroscience 2020, 2020 | 282 | 2020 |
Emotion recognition using eye-tracking: taxonomy, review and current challenges JZ Lim, J Mountstephens, J Teo Sensors 20 (8), 2384, 2020 | 215 | 2020 |
Early detection of silent hypoxia in Covid-19 pneumonia using smartphone pulse oximetry J Teo Journal of medical systems 44 (8), 134, 2020 | 126 | 2020 |
An industrial IoT-based blockchain-enabled secure searchable encryption approach for healthcare systems using neural network A Ali, MA Almaiah, F Hajjej, MF Pasha, OH Fang, R Khan, J Teo, ... Sensors 22 (2), 572, 2022 | 106 | 2022 |
Aesthetic preference recognition of 3D shapes using EEG LH Chew, J Teo, J Mountstephens Cognitive neurodynamics 10, 165-173, 2016 | 93 | 2016 |
Mental health prediction using machine learning: taxonomy, applications, and challenges J Chung, J Teo Applied Computational Intelligence and Soft Computing 2022, 1-19, 2022 | 84 | 2022 |
A review of recent approaches for emotion classification using electrocardiography and electrodermography signals AF Bulagang, NG Weng, J Mountstephens, J Teo Informatics in Medicine Unlocked 20, 100363, 2020 | 82 | 2020 |
Self-adaptive population sizing for a tune-free differential evolution NS Teng, J Teo, MHA Hijazi Soft Computing 13 (7), 709-724, 2009 | 70 | 2009 |
A true annealing approach to the marriage in honey-bees optimization algorithm J Teo, HA Abbass International Journal of Computational Intelligence and Applications 3 (02 …, 2003 | 69 | 2003 |
Progress and challenges in generative product design: A review of systems J Mountstephens, J Teo Computers 9 (4), 80, 2020 | 54 | 2020 |
Multiobjectivity and complexity in embodied cognition J Teo, HA Abbass IEEE Transactions on Evolutionary Computation 9 (4), 337-360, 2005 | 49 | 2005 |
Fast lane detection with randomized hough transform A Saudi, J Teo, MHA Hijazi, J Sulaiman 2008 international symposium on information technology 4, 1-5, 2008 | 48 | 2008 |
A dataset for emotion recognition using virtual reality and EEG (DER-VREEG): Emotional state classification using low-cost wearable VR-EEG headsets NS Suhaimi, J Mountstephens, J Teo Big Data and Cognitive Computing 6 (1), 16, 2022 | 47 | 2022 |
Four-class emotion classification in virtual reality using pupillometry LJ Zheng, J Mountstephens, J Teo Journal of Big Data 7, 1-9, 2020 | 43 | 2020 |
Automatic generation of controllers for embodied legged organisms: A Pareto evolutionary multi-objective approach J Teo, HA Abbass Evolutionary Computation 12 (3), 355-394, 2004 | 41 | 2004 |
Deep learning for EEG-based preference classification J Teo, CL Hou, J Mountstephens AIP Conference Proceedings 1891 (1), 2017 | 39 | 2017 |
Multiclass emotion prediction using heart rate and virtual reality stimuli AF Bulagang, J Mountstephens, J Teo Journal of Big Data 8, 1-12, 2021 | 34 | 2021 |
Classification of affective states via EEG and deep learning J Teo, LH Chew, JT Chia, J Mountstephens International Journal of Advanced Computer Science and Applications 9 (5), 2018 | 30 | 2018 |