Skip to main content

Research Repository

Advanced Search

Muhammad Bilal's Outputs (56)

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 deep learning approach for context-aware citation recommendation using rhetorical zone classification and similarity to overcome cold-start problem (2022)
Journal Article

In the recent decade, the citation recommendation has emerged as an important research topic due to its need for the huge size of published scientific work. Among other citation recommendation techniques, the widely used content-based filtering (CBF)... Read More about A deep learning approach for context-aware citation recommendation using rhetorical zone classification and similarity to overcome cold-start problem.

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.

Integrating single-shot fast gradient sign method (FGSM) with classical image processing techniques for generating adversarial attacks on deep learning classifiers (2022)
Presentation / Conference Contribution

Deep learning architectures have emerged as powerful function approximators in a broad spectrum of complex representation learning tasks, such as, computer vision, natural language processing and collaborative filtering. These architectures bear a hi... Read More about Integrating single-shot fast gradient sign method (FGSM) with classical image processing techniques for generating adversarial attacks on deep learning classifiers.

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.

Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges (2021)
Journal Article

The growth of the construction industry is severely limited by the myriad complex challenges it faces such as cost and time overruns, health and safety, productivity and labour shortages. Also, construction industry is one the least digitized industr... Read More about Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges.

Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations (2020)
Journal Article

© 2020 Elsevier Ltd Forecasting imminent accidents in power infrastructure projects require a robust and accurate prediction model to trigger a proactive strategy for risk mitigation. Unfortunately, getting ready-made machine learning algorithms to e... Read More about Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations.