Dr Saeed Sharif


NameDr Saeed Sharif
Job titleSenior Lecturer
Email addresssaeed3@uel.ac.uk
Research instituteUEL

Research outputs

A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images

Van Druten, J., Sharif, S., Chan, S. S., Chong, C. and Abdalla, H. 2019. A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images. in: Proceedings: 2019 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE.

Context-Aware Driver Distraction Severity Classification using LSTM Network

Fasanmade, A., Aliyu, S., He, Y., Al-Bayatti, A. H., Sharif, S. and Alfakeeh, A. S. 2019. Context-Aware Driver Distraction Severity Classification using LSTM Network. in: Proceedings: 2019 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE.

Predicting the Standard and Deviant Patterns In EEG Signals Based On Deep Learning Model

Sharif, S., Al-Bayatti, A. H. and Alfakeeh, A. S. 2019. Predicting the Standard and Deviant Patterns In EEG Signals Based On Deep Learning Model. in: Proceedings: 2019 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE.

Effect of PET Image Reconstruction Techniques on Unexpected Aorta Uptake

Hirji, H., Sullivan, K., Lasker, I., Sharif, S., Nunes, A., Shepherd, C., Wong, W. and Sanghera, B. 2019. Effect of PET Image Reconstruction Techniques on Unexpected Aorta Uptake. Molecular Imaging and Radionuclide Therapy. 28 (1), pp. 1-7.

Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data

Ebenuwa, S., Sharif, M., Alazab, Mamoun and Al-Nemrat, A. 2019. Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data. IEEE Access. 7, pp. 24649-24666.

Medical data analysis based on Nao robot: An automated approach towards robotic real-time interaction with human body

Sharif, M. and Alsibai, Mohammed Hayyan 2018. Medical data analysis based on Nao robot: An automated approach towards robotic real-time interaction with human body. in: 2017 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) IEEE. pp. 91-96

A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis

van Druten, Jacqueline, Sharif, M., Khashu, Minesh and Abdalla, H. 2019. A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis. in: Miraz, Mahdi H., Exce, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 101-106

A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser

Alsallal, Muna, Sharif, M., Al-Ghzawi, Baydaa and al Mutoki, Sabah Mohammed Mlkat 2019. A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser. in: Miraz, Mahdi H., Excell, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 118-122

An Effective TeleHealth Assistive System to Support Senior Citizen at Home or Care-Homes

Sharif, M., Alsallal, Muna and Herghelegiu, Lucian 2018. An Effective TeleHealth Assistive System to Support Senior Citizen at Home or Care-Homes. in: Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 113-117

Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network

Sharif, M., Naeem, U., Islam, S. and Karami, A. 2018. Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network. in: Arai, Kohei, Kapoor, Supriya and Bhatia, Rahul (ed.) Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2 Springer, Cham.

The Application of a Semantic-Based Process Mining Framework on a Learning Process Domain

Okoye, Kingsley, Islam, S., Naeem, U., Sharif, M., Azam, Muhammad Awais and Karami, A. 2018. The Application of a Semantic-Based Process Mining Framework on a Learning Process Domain. in: Arai, Kohei, Kapoor, Supriya and Bhatia, Rahul (ed.) Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 1 Springer, Cham.

An Innovative EPW Design Using Add-on Features to Meet Malaysian Requirements

Alsibai, Mohammed Hayyan, Sharif, M., Yaakub, Salma and Hamran, Nurul Nadia Nor 2018. An Innovative EPW Design Using Add-on Features to Meet Malaysian Requirements. in: Proceedings of the 7th IEEE International Conference on Control Systems, Computing and Engineering (ICCSCE 2017) Institute of Electrical and Electronics Engineers (IEEE). pp. 180-185

Taskification – Gamification of Tasks

Naeem, U., Islam, S., Sharif, M., Sudakov, Sergey and Azam, Awais 2017. Taskification – Gamification of Tasks. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers ACM. pp. 631-634

SignalSense - Towards Quality Service

Islam, S., Sharif, M., Naeem, U. and Geehan, James 2017. SignalSense - Towards Quality Service. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers ACM. pp. 627-630

CrimeSafe - Helping you stay safe

Islam, S., Naeem, U., Sharif, M. and Dovnarovic, Arnold 2017. CrimeSafe - Helping you stay safe. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers ACM. pp. 642-645

A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing

Pizzamiglio, S., Naeem, U., ur Réhman, Shafiq, Sharif, M., Abdalla, H. and Turner, D. 2017. A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing. Procedia Computer Science. 113, pp. 89-96.

The Future of Enterprise Security with Regards to Mobile Technology and Applications

Tagoe, F. T. and Sharif, M. 2017. The Future of Enterprise Security with Regards to Mobile Technology and Applications. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.

Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles

Seuwou, Patrice, Banissi, Ebad, Ubakanma, George, Sharif, M. and Healey, Ann 2017. Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.

An efficient system for preprocessing confocal corneal images for subsequent analysis

Sharif, M., Qahwaji, Rami, Hayajneh, Sofyan, Ipson, Stanley, Alzubaidi, Rania and Brahma, Arun 2014. An efficient system for preprocessing confocal corneal images for subsequent analysis. in: 2014 14th UK Workshop on Computational Intelligence (UKCI) IEEE.

Artificial Neural Network-Based System for PET Volume Segmentation

Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2010. Artificial Neural Network-Based System for PET Volume Segmentation. International Journal of Biomedical Imaging. 2010 (105610).

Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification

Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2012. Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification. Advances in Fuzzy Systems. 2012 (327861).

Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study

Sharif, M., Abbod, Maysam, Sonoda, Luke I. and Sanghera, Bal 2013. Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study. British Journal of Applied Science & Technology. 4 (4), pp. 634-649.

Preparation of 2D sequences of corneal images for 3D model building

Elbita, Abdulhakim, Qahwaji, Rami, Ipson, Stanley, Sharif, M. and Ghanchi, Faruque 2015. Preparation of 2D sequences of corneal images for 3D model building. Computer Methods and Programs in Biomedicine. 114 (2), pp. 194-205.

Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images

Sharif, M., Qahwaji, R., Ipson, S. and Brahma, A. 2015. Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images. Applied Soft Computing. 36 (Nov.), pp. 269-282.

An efficient intelligent analysis system for confocal corneal endothelium images

Sharif, M., Qahwaji, R., Shahamatnia, E., Alzubaidi, R., Ipson, S. and Brahma, A. 2015. An efficient intelligent analysis system for confocal corneal endothelium images. Computer Methods and Programs in Biomedicine. 122 (3), pp. 421-436.

In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study

Alzubaidi, Rania, Sharif, M., Qahwaji, Rami, Ipson, Stanley and Brahma, Arun 2015. In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study. British Journal of Ophthalmology. 100 (1), pp. 41-55.
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