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A searchable record of ICResG research output — journal articles, conference papers, technical reports and more. Search by author, title, year, venue, DOI, research area or keyword.
13 publications found.
Cite this publication
Akuma, F. C. (2026). Initialisation Strategies and Convergence Behaviour in Federated YOLOV8-Based Object Detection for Intelligent Transportation Systems. https://doi.org/10.1109/CI2A69097.2026.11576985
Akuma, F.C. (2026) 'Initialisation Strategies and Convergence Behaviour in Federated YOLOV8-Based Object Detection for Intelligent Transportation Systems'. doi: 10.1109/CI2A69097.2026.11576985.
F. C. Akuma, "Initialisation Strategies and Convergence Behaviour in Federated YOLOV8-Based Object Detection for Intelligent Transportation Systems," 2026. doi: 10.1109/CI2A69097.2026.11576985.
Akuma FC. Initialisation Strategies and Convergence Behaviour in Federated YOLOV8-Based Object Detection for Intelligent Transportation Systems. 2026. doi: 10.1109/CI2A69097.2026.11576985.
Akuma, Fortune Chijiuka. "Initialisation Strategies and Convergence Behaviour in Federated YOLOV8-Based Object Detection for Intelligent Transportation Systems." 2026. https://doi.org/10.1109/CI2A69097.2026.11576985.
Akuma, F. C.. "Initialisation Strategies and Convergence Behaviour in Federated YOLOV8-Based Object Detection for Intelligent Transportation Systems." (2026). https://doi.org/10.1109/CI2A69097.2026.11576985.
@inproceedings{akuma2026, title={Initialisation Strategies and Convergence Behaviour in Federated YOLOV8-Based Object Detection for Intelligent Transportation Systems}, author={Akuma, Fortune Chijiuka}, year={2026}, doi={10.1109/CI2A69097.2026.11576985}, }
Cite this publication
Akuma, F. C. (2026). Evaluating Centralised and Federated Learning YOLOv8-Based Object Detection for Intelligent Transportation Systems. https://doi.org/10.1109/CI2A69097.2026.11576852
Akuma, F.C. (2026) 'Evaluating Centralised and Federated Learning YOLOv8-Based Object Detection for Intelligent Transportation Systems'. doi: 10.1109/CI2A69097.2026.11576852.
F. C. Akuma, "Evaluating Centralised and Federated Learning YOLOv8-Based Object Detection for Intelligent Transportation Systems," 2026. doi: 10.1109/CI2A69097.2026.11576852.
Akuma FC. Evaluating Centralised and Federated Learning YOLOv8-Based Object Detection for Intelligent Transportation Systems. 2026. doi: 10.1109/CI2A69097.2026.11576852.
Akuma, Fortune Chijiuka. "Evaluating Centralised and Federated Learning YOLOv8-Based Object Detection for Intelligent Transportation Systems." 2026. https://doi.org/10.1109/CI2A69097.2026.11576852.
Akuma, F. C.. "Evaluating Centralised and Federated Learning YOLOv8-Based Object Detection for Intelligent Transportation Systems." (2026). https://doi.org/10.1109/CI2A69097.2026.11576852.
@inproceedings{akuma2026, title={Evaluating Centralised and Federated Learning YOLOv8-Based Object Detection for Intelligent Transportation Systems}, author={Akuma, Fortune Chijiuka}, year={2026}, doi={10.1109/CI2A69097.2026.11576852}, }
DEMO publication — replace with real content. We study cross-lingual transfer from high-resource models to five low-resource African languages, releasing annotated corpora and baseline results for news topic classification.
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Okafor, S. & Akuma, F. C. (2026). Cross-Lingual Transfer for Text Classification in Low-Resource African Languages (DEMO). arXiv (DEMO).
Okafor, S. and Akuma, F.C. (2026) 'Cross-Lingual Transfer for Text Classification in Low-Resource African Languages (DEMO)', arXiv (DEMO).
S. Okafor and F. C. Akuma, "Cross-Lingual Transfer for Text Classification in Low-Resource African Languages (DEMO)," arXiv (DEMO), 2026.
Okafor S, Akuma FC. Cross-Lingual Transfer for Text Classification in Low-Resource African Languages (DEMO). arXiv (DEMO). 2026.
Okafor, Sarah, and Fortune Chijiuka Akuma. "Cross-Lingual Transfer for Text Classification in Low-Resource African Languages (DEMO)." arXiv (DEMO), 2026.
Okafor, S., Akuma, F. C.. "Cross-Lingual Transfer for Text Classification in Low-Resource African Languages (DEMO)." arXiv (DEMO) (2026).
@misc{okafor2026crosslingual, title={Cross-Lingual Transfer for Text Classification in Low-Resource African Languages}, author={Okafor, Sarah and Akuma, Fortune Chijiuka}, year={2026} }
DEMO publication — replace with real content. We evaluate compact convolutional architectures for classifying crop leaf diseases on low-cost smartphones, showing that pruned MobileNet variants retain 95% of full-model accuracy at a fraction of the computational cost.
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Mensah, D., Adeyemi, L., & Okafor, S. (2026). Lightweight Convolutional Models for On-Device Crop Disease Detection (DEMO). Proceedings of the DEMO International Conference on Applied Machine Learning. https://doi.org/10.0000/demo.2026.001
Mensah, D., Adeyemi, L. and Okafor, S. (2026) 'Lightweight Convolutional Models for On-Device Crop Disease Detection (DEMO)', Proceedings of the DEMO International Conference on Applied Machine Learning. doi: 10.0000/demo.2026.001.
D. Mensah, L. Adeyemi, and S. Okafor, "Lightweight Convolutional Models for On-Device Crop Disease Detection (DEMO)," Proceedings of the DEMO International Conference on Applied Machine Learning, 2026. doi: 10.0000/demo.2026.001.
Mensah D, Adeyemi L, Okafor S. Lightweight Convolutional Models for On-Device Crop Disease Detection (DEMO). Proceedings of the DEMO International Conference on Applied Machine Learning. 2026. doi: 10.0000/demo.2026.001.
Mensah, Daniel, et al.. "Lightweight Convolutional Models for On-Device Crop Disease Detection (DEMO)." Proceedings of the DEMO International Conference on Applied Machine Learning, 2026. https://doi.org/10.0000/demo.2026.001.
Mensah, D., Adeyemi, L., Okafor, S.. "Lightweight Convolutional Models for On-Device Crop Disease Detection (DEMO)." Proceedings of the DEMO International Conference on Applied Machine Learning (2026). https://doi.org/10.0000/demo.2026.001.
@inproceedings{mensah2026lightweight, title={Lightweight Convolutional Models for On-Device Crop Disease Detection}, author={Mensah, Daniel and Adeyemi, Lola and Okafor, Sarah}, booktitle={Proc. DEMO Int. Conf. on Applied Machine Learning}, year={2026} }
Cite this publication
Akuma, F. C. (2025). AI Agents: A Comprehensive Review of Evolution, Architectures, Applications, and Future Directions. 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). https://doi.org/10.1109/icrito66076.2025.11241897
Akuma, F.C. (2025) 'AI Agents: A Comprehensive Review of Evolution, Architectures, Applications, and Future Directions', 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). doi: 10.1109/icrito66076.2025.11241897.
F. C. Akuma, "AI Agents: A Comprehensive Review of Evolution, Architectures, Applications, and Future Directions," 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2025. doi: 10.1109/icrito66076.2025.11241897.
Akuma FC. AI Agents: A Comprehensive Review of Evolution, Architectures, Applications, and Future Directions. 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 2025. doi: 10.1109/icrito66076.2025.11241897.
Akuma, Fortune Chijiuka. "AI Agents: A Comprehensive Review of Evolution, Architectures, Applications, and Future Directions." 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2025. https://doi.org/10.1109/icrito66076.2025.11241897.
Akuma, F. C.. "AI Agents: A Comprehensive Review of Evolution, Architectures, Applications, and Future Directions." 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) (2025). https://doi.org/10.1109/icrito66076.2025.11241897.
@inproceedings{akuma2025, title={AI Agents: A Comprehensive Review of Evolution, Architectures, Applications, and Future Directions}, author={Akuma, Fortune Chijiuka}, booktitle={2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)}, year={2025}, doi={10.1109/icrito66076.2025.11241897}, }
Cite this publication
Akuma, F. C. (2025). A Comprehensive Review of Predicting Vaccine Side Effects with AI. 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). https://doi.org/10.1109/icrito66076.2025.11241905
Akuma, F.C. (2025) 'A Comprehensive Review of Predicting Vaccine Side Effects with AI', 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). doi: 10.1109/icrito66076.2025.11241905.
F. C. Akuma, "A Comprehensive Review of Predicting Vaccine Side Effects with AI," 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2025. doi: 10.1109/icrito66076.2025.11241905.
Akuma FC. A Comprehensive Review of Predicting Vaccine Side Effects with AI. 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 2025. doi: 10.1109/icrito66076.2025.11241905.
Akuma, Fortune Chijiuka. "A Comprehensive Review of Predicting Vaccine Side Effects with AI." 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2025. https://doi.org/10.1109/icrito66076.2025.11241905.
Akuma, F. C.. "A Comprehensive Review of Predicting Vaccine Side Effects with AI." 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) (2025). https://doi.org/10.1109/icrito66076.2025.11241905.
@inproceedings{akuma2025, title={A Comprehensive Review of Predicting Vaccine Side Effects with AI}, author={Akuma, Fortune Chijiuka}, booktitle={2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)}, year={2025}, doi={10.1109/icrito66076.2025.11241905}, }
Cite this publication
Akuma, F. C. (2025). Perception: A Systematic Review of Federated Learning for Privacy-Preserving Detection of Mixed Road Users in Intelligent Transportation Systems (ITS). International Journal of Development Mathematics (IJDM). https://doi.org/10.62054/ijdm/0204.12
Akuma, F.C. (2025) 'Perception: A Systematic Review of Federated Learning for Privacy-Preserving Detection of Mixed Road Users in Intelligent Transportation Systems (ITS)', International Journal of Development Mathematics (IJDM). doi: 10.62054/ijdm/0204.12.
F. C. Akuma, "Perception: A Systematic Review of Federated Learning for Privacy-Preserving Detection of Mixed Road Users in Intelligent Transportation Systems (ITS)," International Journal of Development Mathematics (IJDM), 2025. doi: 10.62054/ijdm/0204.12.
Akuma FC. Perception: A Systematic Review of Federated Learning for Privacy-Preserving Detection of Mixed Road Users in Intelligent Transportation Systems (ITS). International Journal of Development Mathematics (IJDM). 2025. doi: 10.62054/ijdm/0204.12.
Akuma, Fortune Chijiuka. "Perception: A Systematic Review of Federated Learning for Privacy-Preserving Detection of Mixed Road Users in Intelligent Transportation Systems (ITS)." International Journal of Development Mathematics (IJDM), 2025. https://doi.org/10.62054/ijdm/0204.12.
Akuma, F. C.. "Perception: A Systematic Review of Federated Learning for Privacy-Preserving Detection of Mixed Road Users in Intelligent Transportation Systems (ITS)." International Journal of Development Mathematics (IJDM) (2025). https://doi.org/10.62054/ijdm/0204.12.
@article{akuma2025, title={Perception: A Systematic Review of Federated Learning for Privacy-Preserving Detection of Mixed Road Users in Intelligent Transportation Systems (ITS)}, author={Akuma, Fortune Chijiuka}, journal={International Journal of Development Mathematics (IJDM)}, year={2025}, doi={10.62054/ijdm/0204.12}, }
Cite this publication
Akuma, F. C. (2025). Forecasting Nigerian Inflation: A SARIMAX and Granger Causality Analysis of Exchange Rate and Crude Oil Price Impacts. International Journal of Development Mathematics (IJDM). https://doi.org/10.62054/ijdm/0204.14
Akuma, F.C. (2025) 'Forecasting Nigerian Inflation: A SARIMAX and Granger Causality Analysis of Exchange Rate and Crude Oil Price Impacts', International Journal of Development Mathematics (IJDM). doi: 10.62054/ijdm/0204.14.
F. C. Akuma, "Forecasting Nigerian Inflation: A SARIMAX and Granger Causality Analysis of Exchange Rate and Crude Oil Price Impacts," International Journal of Development Mathematics (IJDM), 2025. doi: 10.62054/ijdm/0204.14.
Akuma FC. Forecasting Nigerian Inflation: A SARIMAX and Granger Causality Analysis of Exchange Rate and Crude Oil Price Impacts. International Journal of Development Mathematics (IJDM). 2025. doi: 10.62054/ijdm/0204.14.
Akuma, Fortune Chijiuka. "Forecasting Nigerian Inflation: A SARIMAX and Granger Causality Analysis of Exchange Rate and Crude Oil Price Impacts." International Journal of Development Mathematics (IJDM), 2025. https://doi.org/10.62054/ijdm/0204.14.
Akuma, F. C.. "Forecasting Nigerian Inflation: A SARIMAX and Granger Causality Analysis of Exchange Rate and Crude Oil Price Impacts." International Journal of Development Mathematics (IJDM) (2025). https://doi.org/10.62054/ijdm/0204.14.
@article{akuma2025, title={Forecasting Nigerian Inflation: A SARIMAX and Granger Causality Analysis of Exchange Rate and Crude Oil Price Impacts}, author={Akuma, Fortune Chijiuka}, journal={International Journal of Development Mathematics (IJDM)}, year={2025}, doi={10.62054/ijdm/0204.14}, }
DEMO publication — replace with real content. A technical report describing lightweight dataset documentation and versioning practices adopted across ICResG projects, with reusable templates.
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Akuma, F. C. & Adeyemi, L. (2025). Data Documentation Practices for Small Research Groups: Lessons from ICResG (DEMO). ICResG Technical Report Series. https://doi.org/10.0000/demo.2025.041
Akuma, F.C. and Adeyemi, L. (2025) 'Data Documentation Practices for Small Research Groups: Lessons from ICResG (DEMO)', ICResG Technical Report Series. doi: 10.0000/demo.2025.041.
F. C. Akuma and L. Adeyemi, "Data Documentation Practices for Small Research Groups: Lessons from ICResG (DEMO)," ICResG Technical Report Series, 2025. doi: 10.0000/demo.2025.041.
Akuma FC, Adeyemi L. Data Documentation Practices for Small Research Groups: Lessons from ICResG (DEMO). ICResG Technical Report Series. 2025. doi: 10.0000/demo.2025.041.
Akuma, Fortune Chijiuka, and Lola Adeyemi. "Data Documentation Practices for Small Research Groups: Lessons from ICResG (DEMO)." ICResG Technical Report Series, 2025. https://doi.org/10.0000/demo.2025.041.
Akuma, F. C., Adeyemi, L.. "Data Documentation Practices for Small Research Groups: Lessons from ICResG (DEMO)." ICResG Technical Report Series (2025). https://doi.org/10.0000/demo.2025.041.
@techreport{akuma2025data, title={Data Documentation Practices for Small Research Groups: Lessons from ICResG}, author={Akuma, Fortune Chijiuka and Adeyemi, Lola}, institution={ICResG}, year={2025} }
DEMO publication — replace with real content. We present a reproducible benchmark of statistical and neural spatio-temporal models for short-term traffic flow prediction across three open city datasets, with an accompanying open-source toolkit.
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Patel, R. & Kariuki, J. (2025). Benchmarking Spatio-Temporal Models for Urban Traffic Flow Prediction (DEMO). Proceedings of the DEMO Symposium on Intelligent Transportation. https://doi.org/10.0000/demo.2025.032
Patel, R. and Kariuki, J. (2025) 'Benchmarking Spatio-Temporal Models for Urban Traffic Flow Prediction (DEMO)', Proceedings of the DEMO Symposium on Intelligent Transportation. doi: 10.0000/demo.2025.032.
R. Patel and J. Kariuki, "Benchmarking Spatio-Temporal Models for Urban Traffic Flow Prediction (DEMO)," Proceedings of the DEMO Symposium on Intelligent Transportation, 2025. doi: 10.0000/demo.2025.032.
Patel R, Kariuki J. Benchmarking Spatio-Temporal Models for Urban Traffic Flow Prediction (DEMO). Proceedings of the DEMO Symposium on Intelligent Transportation. 2025. doi: 10.0000/demo.2025.032.
Patel, Ravi, and James Kariuki. "Benchmarking Spatio-Temporal Models for Urban Traffic Flow Prediction (DEMO)." Proceedings of the DEMO Symposium on Intelligent Transportation, 2025. https://doi.org/10.0000/demo.2025.032.
Patel, R., Kariuki, J.. "Benchmarking Spatio-Temporal Models for Urban Traffic Flow Prediction (DEMO)." Proceedings of the DEMO Symposium on Intelligent Transportation (2025). https://doi.org/10.0000/demo.2025.032.
@inproceedings{patel2025benchmarking, title={Benchmarking Spatio-Temporal Models for Urban Traffic Flow Prediction}, author={Patel, Ravi and Kariuki, James}, booktitle={Proc. DEMO Symp. on Intelligent Transportation}, year={2025} }