18 papers
A Task-Driven Evaluation of UAV Detection and Tracking under Synthetic Fog
Amir Pouladi, Vesal Ahsani, Haijun Li +2
Fog severely degrades the visibility of small unmanned aerial vehicles (UAVs) in skydominant, long-range imagery, reducing the reliability of downstream detection and tracking. Thi…
SMAC-Talk: A Natural Language Extension of the StarCraft Multi-Agent Challenge for Large Language Models
Joel Sol, Homayoun Najjaran
As LLMs become more widely deployed, they are increasingly expected to work alongside other AI agents rather than operating in isolation. Effective coordination in these settings r…
A Hybrid Intelligent Framework for Uncertainty-Aware Condition Monitoring of Industrial Systems
Maryam Ahang, Todd Charter, Masoud Jalayer +1
Hybrid approaches that combine data-driven learning with physics-based insight have shown promise for improving the reliability of industrial condition monitoring. This work develo…
An Innovative Next Activity Prediction Using Process Entropy and Dynamic Attribute-Wise-Transformer in Predictive Business Process Monitoring
Hadi Zare, Mostafa Abbasi, Maryam Ahang +1
Next activity prediction in predictive business process monitoring is crucial for operational efficiency and informed decision-making. While machine learning and Artificial Intelli…
Sub-Region-Aware Modality Fusion and Adaptive Prompting for Multi-Modal Brain Tumor Segmentation
Shadi Alijani, Fereshteh Aghaee Meibodi, Homayoun Najjaran
The successful adaptation of foundation models to multi-modal medical imaging is a critical yet unresolved challenge. Existing models often struggle to effectively fuse information…
Context Representation via Action-Free Transformer encoder-decoder for Meta Reinforcement Learning
Amir M. Soufi Enayati, Homayoun Honari, Homayoun Najjaran
Reinforcement learning (RL) enables robots to operate in uncertain environments, but standard approaches often struggle with poor generalization to unseen tasks. Context-adaptive m…