Taofeek Akinosho's Outputs (6)

Deep learning-based multi-target regression for traffic-related air pollution forecasting (2023)
Journal Article

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 Contribution

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.

A scalable deep learning system for monitoring and forecasting pollutant concentration levels on UK highways (2022)
Journal Article

The construction of intercity highways by the government has resulted in a progressive increase in vehicle emissions and pollution from noise, dust, and vibrations despite its recognition of the air pollution menace. Efforts that have targeted roadsi... Read More about A scalable deep learning system for monitoring and forecasting pollutant concentration levels on UK highways.

Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting (2021)
Journal Article

Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others. Existing models use complex statis... Read More about Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting.

Deep learning in the construction industry: A review of present status and future innovations (2020)
Journal Article

The construction industry is known to be overwhelmed with resource planning, risk management and logistic challenges which often result in design defects, project delivery delays, cost overruns and contractual disputes. These challenges have instigat... Read More about Deep learning in the construction industry: A review of present status and future innovations.

Complexities of smart city project success: A study of real-life case studies (2019)
Presentation / Conference Contribution

Over the years, the world has moved towards an unprecedented level of urbanisation as half of the world’s total population live in cities. This trajectory of rapid urbanisation has greatly improved the modern economy as well as the standard of living... Read More about Complexities of smart city project success: A study of real-life case studies.