Siphendulwe Zaza

Nicole Oyetunji

Subject: Applied mathematics

Selected Publications [2024, 2025]

• Atemkeng, M. T., Chuma, C., Zaza, S., Nunhokee, C. D., & Smirnov, O. M. (2025). A benchmark analysis of saliency-based explainable deep learning methods for the morphological classification of radio galaxies. arXiv preprint arXiv:2502.17207.
• Zaza, S., Atemkeng, M., Murray, T. S., Filmalter, J. D., & Cowley, P. D. (2025). Unsupervised anomaly detection in large-scale estuarine acoustic telemetry data. arXiv preprint arXiv:2502.01543. Under Review in Ecological Informatics
• Ataei, P., & Atemkeng, M. (2025). Terramycelium: A Reference Architecture for Adaptive Big Data Systems. Under Review in Big Data Mining and Analytics
• Nandutu I, Atemkeng M, Okouma P, Mgqatsa N, Fendji JL, Tchakounte F. Enhancing Highway Security and Wildlife Safety: Mitigating Wildlife-Vehicle Collisions with Deep Learning and Drone Technology. In press; Journal of Intelligent Systems
• Hamlomo, S., Atemkeng, M., Brima, Y., Nunhokee, C., & Baxter, J. (2025). A systematic review of low-rank and local low-rank matrix approximation in big data medical imaging. Neural Computing and Applications, 1-56.
• Ngueajio, M., Aryal, S., Atemkeng, M., Washington, G., & Rawat, D. (2025). Decoding Fake News and Hate Speech: A Survey of Explainable AI Techniques: A Survey of Explainable AI Techniques. ACM Computing Surveys.
• Tchokogoué, T., Noumsi, A. V., Atemkeng, M., & Fono, L. A. (2025). Towards Precision Agriculture: A Dataset for Early Detection of Corn Leaf Pests. Data in Brief, 111394.
• Fadja, A. N., Tagni, A. G. F., Che, S. R., & Atemkeng, M. (2025). A Dataset of Annotated African Plum Images from Cameroon for AI-Based Quality Assessment. Data in Brief, 111351.
• Fendji, J. L. K., Donatien, D., & Atemkeng, M. (2025). Hybrid Profile based Multi-document Text Summarisation. Procedia Computer Science, 252, 862-872.
• Atemkeng, M., Hamlomo, S., Welman, B., Oyetunji, N., Ataei, P., & Fendji, J. L. K. (2025). Ethics of Software Programming with Generative AI: Is Programming without Generative AI always radical?. arXiv preprint arXiv:2408.10554. Accepted in  Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
• M Atemkeng, S Perkins, E Seck, S Makhathini, O Smirnov, L Bester, B Hugo. Lossy Compression of Large-Scale Radio Interferometric Data. https://arxiv.org/abs/2304.07050, Under Review in Monthly Notices of the Royal Astronomical Society
• Brima, Y., & Atemkeng, M. (2024). Saliency-driven explainable deep learning in medical imaging: bridging visual explainability and statistical quantitative analysis. BioData Mining, 17(1), 1-33.
• Atemkeng, M., Osanyindoro, V., Rockefeller, R., Hamlomo, S., Mulongo, J., Ansah-Narh, T., ... & Fadja, A. N. (2024). Ensemble learning and deep learning-based defect detection in power generation plants. Journal of Intelligent Systems, 33(1), 20230283.
• Tchokogoué, T., Noumsi, A. V., Atemkeng, M., Fonkou, M. F. Y., & Fono, L. A. (2024). A robust segmentation method combined with classification algorithms for field-based diagnosis of maize plant phytosanitary state. Journal of Intelligent Systems, 33(1), 20230049.
• Nhlapho, W., Atemkeng, M., Brima, Y., & Ndogmo, J. C. (2024). Bridging the Gap: Exploring Interpretability in Deep Learning Models for Brain Tumor Detection and Diagnosis from MRI Images. Information, 15(4), 182.
• Fadja, A. N., Che, S. R., & Atemkemg, M. (2024). Intelligent Vision System with Pruning and Web Interface for Real-Time Defect Detection on African Plum Surfaces. Information, 15(10), 635.
• Varmantchaonala, C. M., Fendji, J. L. E., Schöning, J., & Atemkeng, M. (2024). Quantum Natural Language Processing: A Comprehensive Survey. IEEE Access.