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ORCIDJohn Q. Gan
Qiang Gan 0001
Person information
- affiliation: University of Essex, School of Computer Science and Electronic Engineering, Colchester, UK
- affiliation (former): University of Southampton, Department of Electronics and Computer Science, UK
- affiliation (1996 - 1997): Nanyang Technological University, Singapore
- affiliation (1993 - 1994): Concordia University, Montreal, Canada
- affiliation (PhD 1991): Southeast University, Department of Biomedical Engineering, Nanjing, China
Other persons with the same name
- Qiang Gan 0002 — Nanjing University, National Key Laboratory for Novel Software Technology, China
- Qiang Gan 0003 — Beijing Institute of Technology, State Key Laboratory of Explosion Science and Technology, China
- Qiang Gan 0004 — Microsoft, STCA NLP Group
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2020 – today
- 2024
[j48]Rukiye Savran Kiziltepe
, John Q. Gan, Juan José Escobar:
Integration of Feature and Decision Fusion With Deep Learning Architectures for Video Classification. IEEE Access 12: 19432-19446 (2024)- [j47]Runkai Zhang, Rong Rong, John Q. Gan, Yun Xu, Haixian Wang, Xiaoyun Wang:
Reliable and fast automatic artifact rejection of Long-Term EEG recordings based on Isolation Forest. Medical Biol. Eng. Comput. 62(2): 521-535 (2024) - 2023
- [j46]Xuemin Tan, Jun Qi, John Q. Gan, Jianglin Zhang, Chao Guo, Fu Wan, Ke Wang:
Multi-filter semi-supervised transformer model for fault diagnosis. Eng. Appl. Artif. Intell. 124: 106498 (2023) - [j45]Rukiye Savran Kiziltepe, John Q. Gan, Juan José Escobar:
A novel keyframe extraction method for video classification using deep neural networks. Neural Comput. Appl. 35(34): 24513-24524 (2023) - [j44]Huiyang Wang, Jiuchuan Jiang, John Q. Gan, Haixian Wang:
Motor Imagery EEG Classification Based on a Weighted Multi-Branch Structure Suitable for Multisubject Data. IEEE Trans. Biomed. Eng. 70(11): 3040-3051 (2023) - [c46]Rahmat Izwan Heroza, John Q. Gan, Haider Raza:
SIA-SMOTE: A SMOTE-Based Oversampling Method with Better Interpolation on High-Dimensional Data by Using a Siamese Network. IWANN (1) 2023: 448-460 - 2022
- [c45]Shih-Kai Hung, John Q. Gan:
Boosting Facial Emotion Recognition by Using GANs to Augment Small Facial Expression Dataset. IJCNN 2022: 1-8 - 2021
- [j43]Shih-Kai Hung, John Q. Gan:
Small facial image dataset augmentation using conditional GANs based on incomplete edge feature input. PeerJ Comput. Sci. 7: e760 (2021) - [j42]Diego A. Aquino Brítez, Andrés Ortiz, Julio Ortega, Javier León, Marco A. Formoso, John Q. Gan, Juan José Escobar:
Optimization of Deep Architectures for EEG Signal Classification: An AutoML Approach Using Evolutionary Algorithms. Sensors 21(6): 2096 (2021) - [c44]Shih-Kai Hung, John Q. Gan:
Facial Image Augmentation from Sparse Line Features Using Small Training Data. IWANN (1) 2021: 547-558 - 2020
- [j41]Maysa Ibrahem Almulla Khalaf, John Q. Gan:
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space. Artif. Intell. Res. 9(1): 45- (2020) - [j40]Upasana Talukdar, Shyamanta M. Hazarika, John Q. Gan:
Adaptation of Common Spatial Patterns based on mental fatigue for motor-imagery BCI. Biomed. Signal Process. Control. 58: 101829 (2020) - [j39]Zhaojie Ju, Jinguo Liu, Yongan Huang, Naoyuki Kubota, John Q. Gan:
Neural networks and learning systems for human machine interfacing. Neurocomputing 390: 196-197 (2020) - [c43]Shih-Kai Hung, John Q. Gan:
Augmentation of Small Training Data Using GANs for Enhancing the Performance of Image Classification. ICPR 2020: 3350-3356 - [c42]Rukiye Savran Kiziltepe, John Q. Gan:
Simple Effective Methods for Decision-Level Fusion in Two-Stream Convolutional Neural Networks for Video Classification. IDEAL (1) 2020: 77-87 - [c41]Arwa M. Basbrain, John Q. Gan:
One-Shot Only Real-Time Video Classification: A Case Study in Facial Emotion Recognition. IDEAL (1) 2020: 197-208 - [c40]Janadhip Jacutprakart, Rukiye Savran Kiziltepe, John Q. Gan, Giorgos Papanastasiou, Alba Garcia Seco de Herrera:
Essex-NLIP at MediaEval Predicting Media Memorability 2020 Task. MediaEval 2020
2010 – 2019
- 2019
- [j38]Maysa Ibrahem Almulla Khalaf, John Q. Gan:
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder. Artif. Intell. Res. 8(1): 41-50 (2019) - [j37]Jesús González, Julio Ortega, Miguel Damas, Pedro Martín-Smith, John Q. Gan:
A new multi-objective wrapper method for feature selection - Accuracy and stability analysis for BCI. Neurocomputing 333: 407-418 (2019) - [j36]Upasana Talukdar, Shyamanta M. Hazarika, John Q. Gan:
Motor imagery and mental fatigue: inter-relationship and EEG based estimation. J. Comput. Neurosci. 46(1): 55-76 (2019) - [c39]Yingjuan Sun, Dongbing Pu, Dongbing Gu, John Q. Gan, Kun Yang:
A Rough Set Classifier Based on Discretization and Attribute Selection. ICNC-FSKD 2019: 229-236 - [c38]Rukiye Savran Kiziltepe, John Q. Gan, Juan José Escobar:
Combining Very Deep Convolutional Neural Networks and Recurrent Neural Networks for Video Classification. IWANN (2) 2019: 811-822 - [c37]Juan José Escobar, Julio Ortega, Miguel Damas, Rukiye Savran Kiziltepe, John Q. Gan:
Energy-Time Analysis of Convolutional Neural Networks Distributed on Heterogeneous Clusters for EEG Classification. IWANN (2) 2019: 895-907 - 2018
- [j35]Xuan Li, John Q. Gan, Haixian Wang:
Collective sparse symmetric non-negative matrix factorization for identifying overlapping communities in resting-state brain functional networks. NeuroImage 166: 259-275 (2018) - [j34]Upasana Talukdar, Shyamanta M. Hazarika, John Q. Gan:
A Kernel Partial least square based feature selection method. Pattern Recognit. 83: 91-106 (2018) - [c36]Arwa Mohammed Basbrain, John Q. Gan, Akihiro Sugimoto, Adrian F. Clark:
A Neural Network Approach to Score Fusion for Emotion Recognition. CEEC 2018: 180-185 - [c35]Lei Wang, John Q. Gan:
Prediction of the 2017 French Election Based on Twitter Data Analysis Using Term Weighting. CEEC 2018: 231-235 - [c34]Maysa I. A. Almulla Khalaf, John Q. Gan:
Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction. IJCCI 2018: 31-38 - 2017
- [j33]Suthira Plansangket, John Q. Gan:
Re-ranking Google search returned web documents using document classification scores. Artif. Intell. Res. 6(1): 59-68 (2017) - [j32]Pedro Martín-Smith, Julio Ortega, Javier Asensio-Cubero, John Q. Gan, Andrés Ortiz:
A supervised filter method for multi-objective feature selection in EEG classification based on multi-resolution analysis for BCI. Neurocomputing 250: 45-56 (2017) - [c33]Lei Wang, John Q. Gan:
Prediction of the 2017 French election based on Twitter data analysis. CEEC 2017: 89-93 - [c32]Arwa M. Basbrain, Inas Al-Taie, Nassr Azeez, John Q. Gan, Adrian F. Clark:
Shallow convolutional neural network for eyeglasses detection in facial images. CEEC 2017: 157-161 - [c31]Arwa M. Basbrain, John Q. Gan, Adrian F. Clark:
Accuracy Enhancement of the Viola-Jones Algorithm for Thermal Face Detection. ICIC (3) 2017: 71-82 - [c30]Yunqiao Wu, John Q. Gan, Haixian Wang:
Identifying Intrinsic Phase Lag in EEG Signals from the Perspective of Wilcoxon Signed-Rank Test. ICONIP (3) 2017: 709-717 - [c29]Julio Ortega, Dragi Kimovski, John Q. Gan, Andrés Ortiz, Miguel Damas:
A Parallel Island Approach to Multiobjective Feature Selection for Brain-Computer Interfaces. IWANN (1) 2017: 16-27 - [c28]Julio Ortega, Andrés Ortiz, Pedro Martín-Smith, John Q. Gan, Jesús González Peñalver:
Deep Belief Networks and Multiobjective Feature Selection for BCI with Multiresolution Analysis. IWANN (1) 2017: 28-39 - 2016
- [j31]Javier Asensio-Cubero, John Q. Gan, Ramaswamy Palaniappan:
Multiresolution analysis over graphs for a motor imagery based online BCI game. Comput. Biol. Medicine 68: 21-26 (2016) - [c27]Maysa I. Abdulhussain, John Q. Gan:
Class-specific pre-trained sparse autoencoders for learning effective features for document classification. CEEC 2016: 36-41 - 2015
- [j30]Suthira Plansangket, John Q. Gan:
A query suggestion method combining TF-IDF and Jaccard Coefficient for interactive web search. Artif. Intell. Res. 4(2): 119-125 (2015) - [j29]Xue-Min Tan, Min-You Chen, John Q. Gan:
A co-training algorithm based on modified Fisher's linear discriminant analysis. Intell. Data Anal. 19(2): 279-292 (2015) - [c26]Adity Saikia, Md. Arif Khan, Sumant Pusph, Syed Ibtisam Tauhidi, Rupam Bhattacharyya, Shyamanta M. Hazarika, John Q. Gan:
cBDI-based Collaborative Control for a Robotic Wheelchair. IHCI 2015: 127-131 - [c25]Pedro Martín-Smith, Julio Ortega Lopera, Javier Asensio-Cubero, John Q. Gan, Andrés Ortiz:
A Label-Aided Filter Method for Multi-objective Feature Selection in EEG Classification for BCI. IWANN (1) 2015: 133-144 - [c24]Julio Ortega, Javier Asensio-Cubero, John Q. Gan, Andrés Ortiz:
Evolutionary Multiobjective Feature Selection in Multiresolution Analysis for BCI. IWBBIO (1) 2015: 347-359 - 2014
- [j28]Hossein Farid Ghassem Nia, Huosheng Hu, John Q. Gan:
A novel fuzzy logic approach to online exposure time calculation of line scan cameras in industrial inspection. Int. J. Model. Identif. Control. 21(1): 8-16 (2014) - [j27]John Q. Gan, Bashar Awwad Shiekh Hasan, Chun Sing Louis Tsui:
A filter-dominating hybrid sequential forward floating search method for feature subset selection in high-dimensional space. Int. J. Mach. Learn. Cybern. 5(3): 413-423 (2014) - [c23]Suthira Plansangket, John Q. Gan:
Performance Evaluation of State-of-the-Art Ranked Retrieval Methods and Their Combinations for Query Suggestion. KDIR 2014: 141-148 - [c22]Lihan Wang, John Q. Gan, Haixian Wang:
CSP-Based EEG Analysis on Dissociated Brain Organization for Single-Digit Addition and Multiplication. ISNN 2014: 131-139 - [c21]Javier Asensio-Cubero, John Q. Gan, Ramaswamy Palaniappan:
Wavelet Lifting over Information-Based EEG Graphs for Motor Imagery Data Classification. PhyCS (Selected Papers) 2014: 3-19 - [c20]Javier Asensio-Cubero, John Q. Gan, Ramaswamy Palaniappan:
Multiresolution Analysis of an Information based EEG Graph Representation for Motor Imagery Brain Computer Interfaces. PhyCS 2014: 5-12 - 2013
- [j26]Javier Asensio-Cubero, John Q. Gan, Ramaswamy Palaniappan:
Extracting optimal tempo-spatial features using local discriminant bases and common spatial patterns for brain computer interfacing. Biomed. Signal Process. Control. 8(6): 772-778 (2013) - [c19]Surej Mouli, Ramaswamy Palaniappan, Ian P. Sillitoe, John Q. Gan:
Performance analysis of multi-frequency SSVEP-BCI using clear and frosted colour LED stimuli. BIBE 2013: 1-4 - [c18]Li Zhang, Haixian Wang, John Q. Gan:
EEG-Based Cortical Localization of Neural Efficiency Related to Mathematical Giftedness. ICONIP (1) 2013: 25-32 - 2012
- [j25]Renato Cordeiro de Amorim, Boris G. Mirkin, John Q. Gan:
Anomalous pattern based clustering of mental tasks with subject independent learning - some preliminary results. Artif. Intell. Res. 1(1): 55-62 (2012) - [j24]Bashar Awwad Shiekh Hasan, John Q. Gan:
Hangman BCI: An unsupervised adaptive self-paced Brain-Computer Interface for playing games. Comput. Biol. Medicine 42(5): 598-606 (2012) - [c17]Noura Al Moubayed, Bashar Awwad Shiekh Hasan, John Q. Gan, Andrei Petrovski, John A. W. McCall:
Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces. IEEE Congress on Evolutionary Computation 2012: 1-7 - 2011
- [j23]Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan:
Bayesian inference for an adaptive Ordered Probit model: An application to Brain Computer Interfacing. Neural Networks 24(7): 726-734 (2011) - [c16]John Q. Gan, Bashar Awwad Shiekh Hasan, Chun Sing Louis Tsui:
A Hybrid Approach to Feature Subset Selection for Brain-Computer Interface Design. IDEAL 2011: 279-286 - 2010
- [j22]Bashar Awwad Shiekh Hasan, John Q. Gan:
Unsupervised movement onset detection from EEG recorded during self-paced real hand movement. Medical Biol. Eng. Comput. 48(3): 245-253 (2010) - [c15]Bashar Awwad Shiekh Hasan, John Q. Gan, Qingfu Zhang:
Multi-objective evolutionary methods for channel selection in Brain-Computer Interfaces: Some preliminary experimental results. IEEE Congress on Evolutionary Computation 2010: 1-6
2000 – 2009
- 2009
- [j21]Shang-Ming Zhou, John Q. Gan, Lida Xu, Robert Ivor John:
Fuzziness index driven fuzzy relaxation algorithm and applications to image processing. Ann. Oper. Res. 168(1): 119-131 (2009) - [j20]Chun Sing Louis Tsui, John Q. Gan, Stephen J. Roberts:
A self-paced brain-computer interface for controlling a robot simulator: an online event labelling paradigm and an extended Kalman filter based algorithm for online training. Medical Biol. Eng. Comput. 47(3): 257-265 (2009) - [j19]Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan:
Adaptive classification for Brain Computer Interface systems using Sequential Monte Carlo sampling. Neural Networks 22(9): 1286-1294 (2009) - [j18]Shang-Ming Zhou, John Q. Gan:
Extracting Takagi-Sugeno Fuzzy Rules with Interpretable Submodels via Regularization of Linguistic Modifiers. IEEE Trans. Knowl. Data Eng. 21(8): 1191-1204 (2009) - [c14]Bashar Awwad Shiekh Hasan, John Q. Gan:
Sequential EM for Unsupervised Adaptive Gaussian Mixture Model Based Classifier. MLDM 2009: 96-106 - 2008
- [j17]Tao Geng, John Q. Gan, Matthew Dyson, Chun Sing Louis Tsui, Francisco Sepulveda:
A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks. Comput. Intell. Neurosci. 2008 (2008) - [j16]Shang-Ming Zhou, John Q. Gan:
Low-level interpretability and high-level interpretability: a unified view of data-driven interpretable fuzzy system modelling. Fuzzy Sets Syst. 159(23): 3091-3131 (2008) - [j15]Shang-Ming Zhou, John Q. Gan, Francisco Sepulveda:
Classifying mental tasks based on features of higher-order statistics from EEG signals in brain-computer interface. Inf. Sci. 178(6): 1629-1640 (2008) - [c13]Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan:
Adaptive Classification by Hybrid EKF with Truncated Filtering: Brain Computer Interfacing. IDEAL 2008: 370-377 - [c12]Ji Won Yoon, Stephen J. Roberts, Matthew Dyson, John Q. Gan:
Sequential Bayesian estimation for adaptive classification. MFI 2008: 601-605 - 2007
- [j14]Shang-Ming Zhou, John Q. Gan, Lida Xu, Robert I. John:
Interactive image enhancement by fuzzy relaxation. Int. J. Autom. Comput. 4(3): 229-235 (2007) - [j13]John Q. Gan, Eric M. Rosales:
Producing interpretable local models in parametric CMAC by regularization. Int. J. Knowl. Based Intell. Eng. Syst. 11(6): 399-408 (2007) - [j12]Shang-Ming Zhou, John Q. Gan:
Constructing L2-SVM-Based Fuzzy Classifiers in High-Dimensional Space With Automatic Model Selection and Fuzzy Rule Ranking. IEEE Trans. Fuzzy Syst. 15(3): 398-409 (2007) - [c11]Chun Sing Louis Tsui, John Q. Gan:
Asynchronous BCI Control of a Robot Simulator with Supervised Online Training. IDEAL 2007: 125-134 - [c10]Chun Sing Louis Tsui, Pei Jia, John Q. Gan, Huosheng Hu, Kui Yuan:
EMG-based hands-free wheelchair control with EOG attention shift detection. ROBIO 2007: 1266-1271 - 2006
- [j11]Shang-Ming Zhou, John Q. Gan:
Constructing accurate and parsimonious fuzzy models with distinguishable fuzzy sets based on an entropy measure. Fuzzy Sets Syst. 157(8): 1057-1074 (2006) - [j10]Shang-Ming Zhou, John Q. Gan:
A new fuzzy relaxation algorithm for image enhancement. Int. J. Knowl. Based Intell. Eng. Syst. 10(3): 181-192 (2006) - [c9]Ben Wang, John Q. Gan:
SC-Tree: An Efficient Structure for High-Dimensional Data Indexing. BNCOD 2006: 164-176 - [c8]John Q. Gan, Shang-Ming Zhou:
A New Fuzzy Membership Function with Applications in Interpretability Improvement of Neurofuzzy Models. ICIC (2) 2006: 183-194 - [p1]Shang-Ming Zhou, John Q. Gan:
Multiple Objective Learning for Constructing Interpretable Takagi-Sugeno Fuzzy Model. Multi-Objective Machine Learning 2006: 385-403 - 2005
- [j9]De Xu, Carlos Antonio Acosta Calderon, John Q. Gan, Huosheng Hu, Min Tan:
An analysis of the inverse kinematics for a 5-DOF manipulator. Int. J. Autom. Comput. 2(2): 114-124 (2005) - [j8]John Q. Gan, Eimei Oyama, Eric M. Rosales, Huosheng Hu:
A complete analytical solution to the inverse kinematics of the Pioneer 2 robotic arm. Robotica 23(1): 123-129 (2005) - [c7]Ben Wang, John Q. Gan:
An Incremental Updating Method for Clustering-Based High-Dimensional Data Indexing. CIS (1) 2005: 495-502 - [c6]Eimei Oyama, Taro Maeda, John Q. Gan, Eric M. Rosales, Karl F. MacDorman, Susumu Tachi, Arvin Agah:
Inverse kinematics learning for robotic arms with fewer degrees of freedom by modular neural network systems. IROS 2005: 1791-1798 - 2004
- [j7]Shang-Ming Zhou, John Q. Gan:
An Unsupervised Kernel Based Fuzzy C-Means Clustering Algorithm With Kernel Normalisation. Int. J. Comput. Intell. Appl. 4(4): 355-374 (2004) - [c5]Shang-Ming Zhou, John Q. Gan:
Interpretability improvement of input space partitioning by merging fuzzy sets based on an entropy measure. FUZZ-IEEE 2004: 287-292 - [c4]Ben Wang, John Q. Gan:
Integration of Projected Clusters and Principal Axis Trees for High-Dimensional Data Indexing and Query. IDEAL 2004: 191-196 - [c3]Shang-Ming Zhou, John Q. Gan:
Mercer Kernel, Fuzzy C-Means Algorithm, and Prototypes of Clusters. IDEAL 2004: 613-618 - 2003
- [c2]Ben Wang, Qiang Gan:
Non-uniform partition strategies for indexing high-dimensional data with different distributions. ISMSE 2003: 13-20 - 2002
- [b1]Chris J. Harris, Xia Hong, Qiang Gan:
Adaptive Modelling, Estimation and Fusion from Data: A Neurofuzzy Approach. Advanced information processing, Springer 2002, ISBN 3-540-42686-8, pp. I-XVI, 1-323 - 2001
- [j6]Chris J. Harris, Qiang Gan:
State estimation and multi-sensor data fusion using data-based neurofuzzy local linearisation process models. Inf. Fusion 2(1): 17-29 (2001) - [j5]Qiang Gan, Chris J. Harris:
A hybrid learning scheme combining EM and MASMOD algorithms for fuzzy local linearization modeling. IEEE Trans. Neural Networks 12(1): 43-53 (2001)
1990 – 1999
- 1999
- [j4]Jun-Sheng Wang, Qiang Gan, Yu Wei, Li Xie:
Cellular neural networks with opposite‐sign templates for image thinning. Int. J. Circuit Theory Appl. 27(2): 229-240 (1999) - [j3]Jie Zhou, Qiang Gan, Adam Krzyzak, Ching Y. Suen:
Recognition of handwritten numerals by Quantum Neural Network with fuzzy features. Int. J. Document Anal. Recognit. 2(1): 30-36 (1999) - [j2]Qiang Gan, Chris J. Harris:
Fuzzy local linearization and local basis function expansion in nonlinear system modeling. IEEE Trans. Syst. Man Cybern. Part B 29(4): 559-565 (1999) - [j1]Qiang Gan, Chris J. Harris:
Linearization and state estimation of unknown discrete-time nonlinear dynamic systems using recurrent neurofuzzy networks. IEEE Trans. Syst. Man Cybern. Part B 29(6): 802-817 (1999) - 1997
- [c1]Jie Zhou, Qiang Gan, Ching Y. Suen:
A High Performance Hand-printed Numeral Recognition System with Verification Module. ICDAR 1997: 293-297
Coauthor Index
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