7 papers
Future Mining: Learning for Safety and Security
Md Sazedur Rahman, Mizanur Rahman Jewel, Sanjay Madria
Mining is rapidly evolving into an AI driven cyber physical ecosystem where safety and operational reliability depend on robust perception, trustworthy distributed intelligence, an…
Explaining the Unseen: Multimodal Vision-Language Reasoning for Situational Awareness in Underground Mining Disasters
Mizanur Rahman Jewel, Mohamed Elmahallawy, Sanjay Madria +1
Underground mining disasters produce pervasive darkness, dust, and collapses that obscure vision and make situational awareness difficult for humans and conventional systems. To ad…
Secure and Privacy-Preserving Federated Learning for Next-Generation Underground Mine Safety
Mohamed Elmahallawy, Sanjay Madria, Samuel Frimpong
Underground mining operations depend on sensor networks to monitor critical parameters such as temperature, gas concentration, and miner movement, enabling timely hazard detection…
Detecting Untargeted Attacks and Mitigating Unreliable Updates in Federated Learning for Underground Mining Operations
Md Sazedur Rahman, Mohamed Elmahallawy, Sanjay Madria +1
Underground mining operations rely on distributed sensor networks to collect critical data daily, including mine temperature, toxic gas concentrations, and miner movements for haza…
LPLgrad: Optimizing Active Learning Through Gradient Norm Sample Selection and Auxiliary Model Training
Shreen Gul, Mohamed Elmahallawy, Sanjay Madria +1
Machine learning models are increasingly being utilized across various fields and tasks due to their outstanding performance and strong generalization capabilities. Nonetheless, th…
DIS-Mine: Instance Segmentation for Disaster-Awareness in Poor-Light Condition in Underground Mines
Mizanur Rahman Jewel, Mohamed Elmahallawy, Sanjay Madria +1
Detecting disasters in underground mining, such as explosions and structural damage, has been a persistent challenge over the years. This problem is compounded for first responders…