Dr Amina Souag
| Name | Dr Amina Souag |
|---|---|
| Job title | Lecturer in Computing |
| Research institute | School of Engineering, Technology and Design |
Research outputs
A hybrid machine learning approach for enhanced skin cancer diagnosis using convolutional neural networks, support vector machines, and gradient boosting
Souag, A. and Olowolayemo, A. 2025. A hybrid machine learning approach for enhanced skin cancer diagnosis using convolutional neural networks, support vector machines, and gradient boosting. in: Sztandera, L. (ed.) AIHealth 2025: The Second International Conference on AI-Health ThinkMind. pp. 35-51Evaluating the impact of machine learning platforms on cancer classification model performance: A cross-platform comparative study
Olowolayemo, A., Souag, A. and Sirlantzis, K. 2024. Evaluating the impact of machine learning platforms on cancer classification model performance: A cross-platform comparative study. International Journal on Advanced in Life Sciences. 16 (no 3 & 4), pp. 96 - 111.Machine learning in ASL fingerspelling recognition: A literature review
Pinnington, J., Souag, A. and Azhar, H. 2024. Machine learning in ASL fingerspelling recognition: A literature review. in: 2024 IEEE 24th International Symposium on Computational Intelligence and Informatics (CINTI) IEEE.Utilising transformers for American Sign Language fingerspelling recognition
Pinnington, Jamie, Souag, A. and Azhar, H. 2024. Utilising transformers for American Sign Language fingerspelling recognition. in: 2024 IEEE 24th International Symposium on Computational Intelligence and Informatics (CINTI) IEEE. pp. 000129-000134A novel dataset of annotated oyster mushroom images with environmental context for machine learning applications
Duman, S., Elewi, A., Hajhamed, A., Khankan, R., Souag, A. and Ahmed, A. 2024. A novel dataset of annotated oyster mushroom images with environmental context for machine learning applications. Data in Brief. 57. https://doi.org/10.1016/j.dib.2024.111074Design and implementation of a cost-aware and smart oyster mushroom cultivation system
Souag, A., Elewi, A., Hajhamed, A., Khankan, R., Duman, S. and Ahmed, A. 2024. Design and implementation of a cost-aware and smart oyster mushroom cultivation system. Smart Agricultural Technology. Volume 8. https://doi.org/10.1016/j.atech.2024.100439Cancer: Investigating the impact of the implementation platform on machine learning models
Olowolayemo, A. S., Souag, A. and Sirlantzis, K. 2024. Cancer: Investigating the impact of the implementation platform on machine learning models. in: Mengoni, M. and Souag, A. (ed.) AIHealth 2024, The First International Conference on AI-Health ThinkMind.AIHealth 2024, Proceedings of The First International Conference on AI-Health
Souag, A. and Mengoni, M. (ed.) 2024. AIHealth 2024, Proceedings of The First International Conference on AI-Health. Athens, Greece ThinkMind.AMAN-DA: A knowledge reuse based approach for domain specific security requirements engineering
Souag, A. 2015. AMAN-DA: A knowledge reuse based approach for domain specific security requirements engineering. PhD Thesis Université Paris 1 Panthéon-Sorbonne CRI - Centre de Recherche en Informatique de Paris 1How can the semantic web and ontologies help history and archeology
Souag, A. 2019. How can the semantic web and ontologies help history and archeology. in: Dans les dédales du web. Historiens en territoires numériques Paris Éditions de la Sorbonne.A security ontology for security requirements elicitation
Souag, A. and Salinesi C., Mazo R., Comyn-Wattiau I. 2015. A security ontology for security requirements elicitation. https://doi.org/10.1007/978-3-319-15618-7_13Ontologies for security requirements: a literature survey and classification’
Souag, A. and Salinesi C., Comyn-Wattiau I. 2012. Ontologies for security requirements: a literature survey and classification’. https://doi.org/10.1007/978-3-642-31069-0_5Why should everybody learn Artificial Intelligence?
Turner, S. and Souag, A. 2022. Why should everybody learn Artificial Intelligence? ETD blog, Canterbury Christ church UniversityUsing the AMAN-DA method to generate security requirements: a case study in the maritime domain
Souag, A., Mazo, R., Salinesi, C. and Comyn-Wattiau, I. 2018. Using the AMAN-DA method to generate security requirements: a case study in the maritime domain. Requirements Engineering Journal. 23 (557–580). https://doi.org/10.1007/s00766-017-0279-5Reusable knowledge in security requirements engineering: a systematic mapping study
Souag, A., Mazo, R., Salinesi, C. and Comyn-Wattiau, I. 2016. Reusable knowledge in security requirements engineering: a systematic mapping study. Requirements Engineering Journal. 21 (251–283). https://doi.org/10.1007/s00766-015-0220-8A methodology for defining security requirements using security and domain ontologies
Souag, A., Salinesi C. and Comyn-Wattiau I. 2013. A methodology for defining security requirements using security and domain ontologies. Insight. Volume 16 (4), pp. 14-16. https://doi.org/10.1002/inst.2013164141439
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