All Outputs (2)

Deep learning-based multi-target regression for traffic-related air pollution forecasting (2023)
Journal Article
Akinosho, T. D., Bilal, M., Hayes, E. T., Ajayi, A., Ahmed, A., & Khan, Z. (2023). Deep learning-based multi-target regression for traffic-related air pollution forecasting. Machine Learning with Applications, 12, Article 100474. https://doi.org/10.1016/j.mlwa.2023.100474

Traffic-related air pollution (TRAP) remains one of the main contributors to urban pollution and its impact on climate change cannot be overemphasised. Experts in developed countries strive to make optimal use of traffic and air qua... Read More about Deep learning-based multi-target regression for traffic-related air pollution forecasting.

SegCrop: Segmentation-based dynamic cropping of endoscopic videos to address label leakage in surgical tool detection (2023)
Presentation / Conference
Qayyum, A., Bilal, M., Qadir, J., Caputo, M., Vohra, H., Akinosho, T., …Abioye, S. (2023, April). SegCrop: Segmentation-based dynamic cropping of endoscopic videos to address label leakage in surgical tool detection. Paper presented at IEEE International Symposium on Biomedical Imaging (ISBI), 2023, Colombia

In recent times, surgical data science has emerged as an important research discipline in interventional healthcare. There are many potential applications for analysing endoscopic surgical videos using machine learning (ML) techniques such as surgica... Read More about SegCrop: Segmentation-based dynamic cropping of endoscopic videos to address label leakage in surgical tool detection.