Dr Daqing Chen


NameDr Daqing Chen
Job titleSenior Lecturer
Organisational UnitComputer Science and Informatics
ORCIDhttps://orcid.org/0000-0003-0030-1199

Research outputs

Deep Learning-based Automated Lip-Reading: A Survey

Fenghour, S., Chen, D., Guo, K., Li, B. and Xiao, P. (2021). Deep Learning-based Automated Lip-Reading: A Survey. IEEE Access.

Deep Learning Causal Attributions of Breast Cancer

Chen, D., Hajderanj, L., Mallet, S., Camenen, P., Li, B., Hao, R. and Zhao, E. (2021). Deep Learning Causal Attributions of Breast Cancer. in: Arai, K. (ed.) Intelligent Computing, Proceedings of the 2021 Computing Conference, Lecture Notes in Networks and Systems, Vol 285, Intelligent Computing (A. Kohei, Editor) Springer.

Deep Learning Causal Attributions of Breast Cancer

Chen, D, Hajderanj, L, Mallet, S, Camenen, P, Li, B, Ren, H and Zhao, E (2020). Deep Learning Causal Attributions of Breast Cancer. Computing 2021. London 15 - 16 Jul 2021 The Science and Information (SAI) Organization. https://doi.org/10.1007/978-3-030-80129-8_10

The Impact of Supervised Manifold Learning on Structure Preserving and Classification Error: A Theoretical Study

Hajderanj, L., Chen, D. and Weheliye, I. (2021). The Impact of Supervised Manifold Learning on Structure Preserving and Classification Error: A Theoretical Study. IEEE Access. 9. https://doi.org/10.1109/ACCESS.2021.3066259

Enhancing Transformer-based language models with Commonsense Representations for Knowledge-driven Machine Comprehension

Li, R., Jiang, Z., Wang, L., Lu, X., Zhao, M. and Chen, D. (2021). Enhancing Transformer-based language models with Commonsense Representations for Knowledge-driven Machine Comprehension. Knowledge-Based Systems. 220, p. 106936. https://doi.org/10.1016/j.knosys.2021.106936

Maneuvering target tracking of UAV based on MN-DDPG and transfer learning

Li, B., Yang, Z.P., Chen, D.Q., Liang, S.Y. and Ma, H. (2020). Maneuvering target tracking of UAV based on MN-DDPG and transfer learning. Defence Technology. https://doi.org/10.1016/j.dt.2020.11.014

Lip Reading Sentences Using Deep Learning with Only Visual Cues

Fanghour, S., Chen, D., Guo, K. and Xiao, P. (2020). Lip Reading Sentences Using Deep Learning with Only Visual Cues. IEEE Access. https://doi.org/10.1109/ACCESS.2020.3040906

UAV Maneuvering Target Tracking in Uncertain Environments based on Deep Reinforcement Learning and Meta-learning

Li, B., Gan, Z., Chen, D. and Aleksandrovich, D.S. (2020). UAV Maneuvering Target Tracking in Uncertain Environments based on Deep Reinforcement Learning and Meta-learning. Remote Sensing. 12 (22), p. 3789. https://doi.org/10.3390/rs12223789

Single- and Multi-Distribution Dimensionality Reduction Approaches for a Better Data Structure Capturing

Hajderanj, L., Chen, D., Grisan, E. and Dudley-McEvoy, S (2020). Single- and Multi-Distribution Dimensionality Reduction Approaches for a Better Data Structure Capturing. IEEE Access. 8, pp. 207141 - 207155. https://doi.org/10.1109/ACCESS.2020.3038460

Learning Bayesian Networks based on Order Graph with Ancestral Constraints

Wang, Z., Gao, X., Tian, X., Yang, Y. and Chen, D. (2020). Learning Bayesian Networks based on Order Graph with Ancestral Constraints. Knowledge-Based Systems. https://doi.org/10.1016/j.knosys.2020.106515

The Development of a Skin Image Analysis Tool by Using Machine Learning Algorithms

Xiao, P., Zhang, Xu, Pan, Wei, Ou, Xiang, Bontozoglou, C., Chirikhina, E. and Chen, D. (2020). The Development of a Skin Image Analysis Tool by Using Machine Learning Algorithms. Cosmetics. 7 (3), p. e67. https://doi.org/10.3390/cosmetics7030067

Skin Capacitive Imaging Analysis Using Deep Learning GoogLeNet

Zhang, X., Pan, W., Bontozoglou, C., Chirikhina, E., Chen, D. and Xiao, P. (2019). Skin Capacitive Imaging Analysis Using Deep Learning GoogLeNet. Computing Conference 2020. London, UK 16 - 17 Jul 2019 Springer.

Effectiveness analysis of ship formation air defence based on deep belief network

Li, B., Luo, H., Wang, Y. and Chen, D. (2020). Effectiveness analysis of ship formation air defence based on deep belief network. The Journal of Engineering. 2020 (13), pp. 394-398. https://doi.org/10.1049/joe.2019.1201

An adaptive dwell time scheduling model for phased array radar based on three-way decision

Li, B., Tian, L., Chen, D. and Liang, S. (2020). An adaptive dwell time scheduling model for phased array radar based on three-way decision. Journal of Systems Engineering and Electronics. pp. 500-509. https://doi.org/10.23919/JSEE.2020.000030

Three‐way decision of target threat decision making based on adaptive threshold algorithms

Li, B., Tian, Li., Han, Y. and Chen, D. (2020). Three‐way decision of target threat decision making based on adaptive threshold algorithms. The Journal of Engineering. 2020 (13), pp. 293-297. https://doi.org/10.1049/joe.2019.1202

An Adaptive Task Scheduling Method for Networked UAV Combat Cloud System Based on Virtual Machine and Task Migration

Li, B., Liang, S., Tian, L., Chen, D. and Zhang, M. (2020). An Adaptive Task Scheduling Method for Networked UAV Combat Cloud System Based on Virtual Machine and Task Migration. Mathematical Problems in Engineering. p. 5391479. https://doi.org/10.1155/2020/5391479

A Task Scheduling Algorithm for Phased Array Radar Based on Dynamic Three-way Decision

Li, B., Tian, L., Chen, D. and Han, Y. (2019). A Task Scheduling Algorithm for Phased Array Radar Based on Dynamic Three-way Decision. Sensors. 20 (1). https://doi.org/10.3390/s20010153

Intelligent Aircraft Maneuvering Decision Based on CNN

Li, B., Liang, S., Tian, L. and Chen, D. (2019). Intelligent Aircraft Maneuvering Decision Based on CNN. Proceedings of the 3rd International Conference on Computer Science and Application Engineering. (138). https://doi.org/10.1145/3331453.3362046

Predicting Customer Profitability Dynamically over Time: An Experimental Comparative Study

Chen, D., Guo, K. and Li, B. (2019). Predicting Customer Profitability Dynamically over Time: An Experimental Comparative Study. 24th Iberoamerican Congress on Pattern Recognition (CIARP 2019). Havana, Cuba 28 - 31 Oct 2019 https://doi.org/10.1007/978-3-030-33904-3_16

Intelligent Attitude Control of Aircraft Based on LSTM

Li, B, Gao, P, Li, X and Chen, D (2019). Intelligent Attitude Control of Aircraft Based on LSTM. 3rd International Conference on Artificial Intelligence Applications and Technologies. Beijing, China 01 - 03 Aug 2019 IOP Publishing. https://doi.org/10.1088/1757-899X/646/1/012013

FRS: A Simple Knowledge Graph Embedding Model for Entity Prediction

Wang, L.F., Lu, X., Jiang, Z., Zhang, Z., Li, R., Zhao, M. and Chen, D. (2019). FRS: A Simple Knowledge Graph Embedding Model for Entity Prediction. Mathematical Biosciences and Engineering. 16 (6), pp. 7789-7807. https://doi.org/10.3934/mbe.2019391

Design of a voice control 6DoF grasping robotic arm based on ultrasonic sensor, computer vision and Alexa voice assistance

Wang, Z, Chen, D and Xiao, P (2019). Design of a voice control 6DoF grasping robotic arm based on ultrasonic sensor, computer vision and Alexa voice assistance. International Conference on Information Technology in Medicine and Education. Qingdao, China 23 - 25 Aug 2019 IEEE. https://doi.org/10.1109/ITME.2019.00150

Intelligent Flight Control of Combat Aircraft Based on Autoencoder

Li, B., Gao, P., Liang, S. and Chen, D. (2019). Intelligent Flight Control of Combat Aircraft Based on Autoencoder. 2019 The 4th International Conference on Robotics, Control and Automation. GuangZhou 26 - 28 Jul 2019 https://doi.org/10.1145/3351180.3351210

Towards automated cost analysis, benchmarking and estimating in construction: a machine learning approach

Chen, D, Hajderanj, L and Fiske, J (2019). Towards automated cost analysis, benchmarking and estimating in construction: a machine learning approach. 13th Multi Conference on Computer Science and Information Systems (MCCSIS). Porto, Portugal 16 - 18 Jul 2019

Improving Prediction Accuracy of Breast Cancer Survivability and Diabetes Diagnosis via RBF Networks trained with EKF models

Adegoke, V, Chen, D and Banissi, E (2019). Improving Prediction Accuracy of Breast Cancer Survivability and Diabetes Diagnosis via RBF Networks trained with EKF models. International Journal of Computer Information Systems and Industrial Management.

Distributed deep networks based on Bagging-Down SGD algorithm

Qin, C, Gao, X and Chen, D (2019). Distributed deep networks based on Bagging-Down SGD algorithm. Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics. 41 (5), pp. 1021-1027. https://doi.org/10.3969/j.issn.1001-506X.2019.05.13

Enhancing Ensemble Prediction Accuracy of Breast Cancer Survivability and Diabetes Diagnostic using optimized EKF-RBFN trained prototypes, The 10th International Conference on Soft Computing and Pattern Recognition

Adegoke, V, Chen, D, Banissi, E and Barikzai, S (2019). Enhancing Ensemble Prediction Accuracy of Breast Cancer Survivability and Diabetes Diagnostic using optimized EKF-RBFN trained prototypes, The 10th International Conference on Soft Computing and Pattern Recognition. The 10th International Conference on Soft Computing and Pattern Recognition. Porto, Portugal 13 - 15 Dec 2018

A New Supervised t-SNE with Dissimilarity Measure for Effective Data Visualization and Classification

Hajderanj, L, Weheliye, I and Chen, D (2019). A New Supervised t-SNE with Dissimilarity Measure for Effective Data Visualization and Classification. 2019 8th International Conference on Software and Information Engineering. Cairo 09 - 12 Apr 2019

Recurrent Neural Networks for Decoding Lip Read Speech

Fenghour, S, Chen, D and Xiao, P (2019). Recurrent Neural Networks for Decoding Lip Read Speech. 2019 8th International Conference on Software and Information Engineering (ICSIE 2019). Cairo 09 - 12 Apr 2019

Learning Bayesian network parameters via minimax algorithm

Gao, X, Gao, G, Ren, H, Chen, D and He, C (2019). Learning Bayesian network parameters via minimax algorithm. International Journal of Approximate Reasoning. 108, pp. 62-75. https://doi.org/10.1016/j.ijar.2019.03.001

Learning Bayesian Networks using the Constrained Maximum a Posteriori Probability Method

Yang, Y, Gao, X, Guo, Z and Chen, D (2019). Learning Bayesian Networks using the Constrained Maximum a Posteriori Probability Method. Pattern Recognition. 91, pp. 123-134. https://doi.org/10.1016/j.patcog.2019.02.006

Contour Mapping for Speaker-Independent Lip Reading System

Fenghour, S, Chen, D and Xiao, P (2018). Contour Mapping for Speaker-Independent Lip Reading System. The 11th International Conference on Machine Vision (ICMV 2018). Munich, Germany 01 - 03 Nov 2018

Visual analytics in the public sector: An analysis on diversities and similarities of London’s wards

Chen, D, Sanz, BM and Zhao, E (2018). Visual analytics in the public sector: An analysis on diversities and similarities of London’s wards. International Conference on Big Data Analytics, Data Mining and Computational Intelligence 2018 (BigDaCI 2018). Madrid, Spain 18 - 20 Jul 2018 Bigdaci.

Predictive Ensemble Modelling: An Experimental Comparison of Boosting Implementation Methods

Adegoke, V, Chen, D, Barikzai, S and Banissi, E (2017). Predictive Ensemble Modelling: An Experimental Comparison of Boosting Implementation Methods. 2017 European Modelling Symposium (EMS). Manchester 20 - 21 Nov 2017

Prediction of Breast Cancer Survivability using Ensemble Algorithms

Adegoke, V, Chen, D, Banissi, E and Barikzai, S (2017). Prediction of Breast Cancer Survivability using Ensemble Algorithms. International Conference on Smart System and Technologies 2017 (SST 2017),. Osijek, Croatia 18 - 20 Oct 2017

Feature Extraction and Labelling Large Data Sets Using Deep Learning

Chen, D (2017). Feature Extraction and Labelling Large Data Sets Using Deep Learning. RESEARCHER LINK: Smart Technology for Fighting Virus Epidemics & Bioinformatics. Recife, Pernambuco, Brazil 10 - 13 Sep 2017

Learning Bayesian Network Parameters from a Small Data Set: A Further Constrained Qualitatively Maximum a Posteriori Method

Guo, Zhi-gao, Gao, Xiao-guang, Hao, Ren, Yang, Yu, Di, Ruo-hai and Chen, D (2017). Learning Bayesian Network Parameters from a Small Data Set: A Further Constrained Qualitatively Maximum a Posteriori Method. International Journal of Approximate Reasoning. 91 (Dec), pp. 22-35. https://doi.org/10.1016/j.ijar.2017.08.009

A Bayesian Approach to Learn Bayesian Networks Using Data and Constraints

Gao, X, Yu, Y, Zhi-gao, G and Chen, D (2016). A Bayesian Approach to Learn Bayesian Networks Using Data and Constraints. 23rd International Conference on Pattern Recognition (ICPR 2016). Cancún, México 04 - 08 Dec 2016 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICPR.2016.7900204

On Distributed Deep Network for Processing Large-Scale Sets of Complex Data

Qin, C, Gao, X and Chen, D (2016). On Distributed Deep Network for Processing Large-Scale Sets of Complex Data. 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). Hangzhou, China. 27 - 28 Aug 2016 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IHMSC.2016.55

On Distributed Deep Network for Processing Large-Scale Sets of Complex Data

Chen, D (2016). On Distributed Deep Network for Processing Large-Scale Sets of Complex Data. 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). Hangzhou, China 27 - 28 Aug 2016

Big Data Analytics In The Public Sector: A Case Study Of NEET Analysis For The London Boroughs

Chen, D, Asaolu, B and Qin, C (2016). Big Data Analytics In The Public Sector: A Case Study Of NEET Analysis For The London Boroughs. International Conference on Big Data Analytics, Data Mining and Computational Intelligence. Funchal, Madeira, Portugal 02 - 04 Jul 2016

Making Better Use of Big Data

Chen, D (2016). Making Better Use of Big Data. LSBU Enterprise Count Event, March 2016. London Southbank University 18 - 18 Mar 2016 London South Bank University.

Big Data Analytics System for Fact/Data-driven Decision Making

Chen, D (2015). Big Data Analytics System for Fact/Data-driven Decision Making. The Royal Statistical Society, Business and Industry Section. London, UK 18 Nov 2015 Royal Statistical Society .

Determining Key (Predictor) Modules for Early Identification of Students At-Risk

Chen, D and Elliott, G (2013). Determining Key (Predictor) Modules for Early Identification of Students At-Risk. International Conference on Advanced Information Engineering and Education Science (ICAIEES 2013). Beijing, China 19 - 20 Dec 2013 Atlantis Press. https://doi.org/10.2991/icaiees-13.2013.22

Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining

Chen, D (2012). Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining. Journal of Database Marketing and Customer Strategy Management. 19 (3), pp. 197-208. https://doi.org/10.1057/dbm.2012.17
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