5 papers
Physics-Informed Graph Neural Networks for Transverse Momentum Estimation in CMS Trigger Systems
Md Abrar Jahin, Shahriar Soudeep, M. F. Mridha +2
Real-time particle transverse momentum () estimation in high-energy physics demands algorithms that are both efficient and accurate under strict hardware constraints. Static m…
DyCAF-Net: Dynamic Class-Aware Fusion Network
Md Abrar Jahin, Shahriar Soudeep, M. F. Mridha +2
Recent advancements in object detection rely on modular architectures with multi-scale fusion and attention mechanisms. However, static fusion heuristics and class-agnostic attenti…
Vision Transformers for End-to-End Quark-Gluon Jet Classification from Calorimeter Images
Md Abrar Jahin, Shahriar Soudeep, Arian Rahman Aditta +3
Distinguishing between quark- and gluon-initiated jets is a critical and challenging task in high-energy physics, pivotal for improving new physics searches and precision measureme…
Interpretable Dynamic Graph Neural Networks for Small Occluded Object Detection and Tracking
Shahriar Soudeep, Md Abrar Jahin, M. F. Mridha
The detection and tracking of small, occluded objects such as pedestrians, cyclists, and motorbikes pose significant challenges for traffic surveillance systems because of their er…
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion Detection
Md Abrar Jahin, Shahriar Soudeep, Fahmid Al Farid +4
Cybersecurity threats are growing, making network intrusion detection essential. Traditional machine learning models remain effective in resource-limited environments due to their…