2 citations · 5 across the 11 of their papers we have counts for
11 papers
Vision-Based Natural Language Scene Understanding for Autonomous Driving: An Extended Dataset and a New Model for Traffic Scene Description Generation
Danial Sadrian Zadeh, Otman A. Basir, Behzad Moshiri
Traffic scene understanding is essential for enabling autonomous vehicles to accurately perceive and interpret their environment, thereby ensuring safe navigation. This paper prese…
NeuroVascU-Net: A Unified Multi-Scale and Cross-Domain Adaptive Feature Fusion U-Net for Precise 3D Segmentation of Brain Vessels in Contrast-Enhanced T1 MRI
Mohammad Jafari Vayeghan, Niloufar Delfan, Mehdi Tale Masouleh +2
Precise 3D segmentation of cerebral vasculature from T1-weighted contrast-enhanced (T1CE) MRI is crucial for safe neurosurgical planning. Manual delineation is time-consuming and p…
Vision Transformer for Intracranial Hemorrhage Classification in CT Scans Using an Entropy-Aware Fuzzy Integral Strategy for Adaptive Scan-Level Decision Fusion
Mehdi Hosseini Chagahi, Md. Jalil Piran, Niloufar Delfan +2
Intracranial hemorrhage (ICH) is a critical medical emergency caused by the rupture of cerebral blood vessels, leading to internal bleeding within the skull. Accurate and timely cl…
Enhancing Precision of Automated Teller Machines Network Quality Assessment: Machine Learning and Multi Classifier Fusion Approaches
Alireza Safarzadeh, Mohammad Reza Jamali, Behzad Moshiri
Ensuring reliable ATM services is essential for modern banking, directly impacting customer satisfaction and the operational efficiency of financial institutions. This study introd…
An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus
Mohammad Fatahi, Danial Sadrian Zadeh, Benyamin Ghojogh +2
Intelligent transportation systems (ITS) play a pivotal role in modern infrastructure but face security risks due to the broadcast-based nature of the in-vehicle Controller Area Ne…
AI-Driven Non-Invasive Detection and Staging of Steatosis in Fatty Liver Disease Using a Novel Cascade Model and Information Fusion Techniques
Niloufar Delfan, Pardis Ketabi Moghadam, Mohammad Khoshnevisan +8
Non-alcoholic fatty liver disease (NAFLD) is one of the most widespread liver disorders on a global scale, posing a significant threat of progressing to more severe conditions like…
AI-Powered Intracranial Hemorrhage Detection: A Co-Scale Convolutional Attention Model with Uncertainty-Based Fuzzy Integral Operator and Feature Screening
Mehdi Hosseini Chagahi, Niloufar Delfan, Behzad Moshiri +2
Intracranial hemorrhage (ICH) refers to the leakage or accumulation of blood within the skull, which occurs due to the rupture of blood vessels in or around the brain. If this cond…
Enhancing Osteoporosis Detection: An Explainable Multi-Modal Learning Framework with Feature Fusion and Variable Clustering
Mehdi Hosseini Chagahi, Saeed Mohammadi Dashtaki, Niloufar Delfan +5
Osteoporosis is a common condition that increases fracture risk, especially in older adults. Early diagnosis is vital for preventing fractures, reducing treatment costs, and preser…
Explainable AI for Fraud Detection: An Attention-Based Ensemble of CNNs, GNNs, and A Confidence-Driven Gating Mechanism
Mehdi Hosseini Chagahi, Niloufar Delfan, Saeed Mohammadi Dashtaki +2
The rapid expansion of e-commerce and the widespread use of credit cards in online purchases and financial transactions have significantly heightened the importance of promptly and…
A Multisource Fusion Framework for Cryptocurrency Price Movement Prediction
Saeed Mohammadi Dashtaki, Reza Mohammadi Dashtaki, Mehdi Hosseini Chagahi +2
Predicting cryptocurrency price trends remains a major challenge due to the volatility and complexity of digital asset markets. Artificial intelligence (AI) has emerged as a powerf…
Deep Representation of Imbalanced Spatio-temporal Traffic Flow Data for Traffic Accident Detection
Pouya Mehrannia, Shayan Shirahmad Gale Bagi, Behzad Moshiri +1
Automatic detection of traffic accidents has a crucial effect on improving transportation, public safety, and path planning. Many lives can be saved by the consequent decrease in t…