2 citations · 3 across the 9 of their papers we have counts for
10 papers
Edge Physical AI Deployment of Vision Transformers on Heterogeneous Edge GPU Targeting Autonomous Vehicles
Ashiyana Abdul Majeed, Mahmoud Meribout, Neethu Joseph +2
Physical AI systems, such as autonomous vehicles and intelligent machines, require transformer-based perception models that satisfy stringent edge latency and energy constraints. H…
Edge GPU Aware Multiple AI Model Pipeline for Accelerated MRI Reconstruction and Analysis
Ashiyana Abdul Majeed, Mahmoud Meribout, Safa Mohammed Sali
Advancements in AI have greatly enhanced the medical imaging process, making it quicker to diagnose patients. However, very few have investigated the optimization of a multi-model…
Hardware Acceleration in Portable MRIs: State of the Art and Future Prospects
Omar Al Habsi, Safa Mohammed Sali, Anis Meribout +3
There is a growing interest in portable MRI (pMRI) systems for point-of-care imaging, particularly in remote or resource-constrained environments. However, the computational comple…
Real-time Object Detection and Associated Hardware Accelerators Targeting Autonomous Vehicles: A Review
Safa Sali, Anis Meribout, Ashiyana Majeed +4
The efficiency of object detectors depends on factors like detection accuracy, processing time, and computational resources. Processing time is crucial for real-time applications,…
Real Time FPGA Based Transformers & VLMs for Vision Tasks: SOTA Designs and Optimizations
Safa Mohammed Sali, Mahmoud Meribout, Ashiyana Abdul Majeed
Transformers and vision-language models (VLMs) have emerged as dominant architectures in computer vision and multimodal AI, offering state-of-the-art performance in tasks such as i…
Real Time FPGA Based CNNs for Detection, Classification, and Tracking in Autonomous Systems: State of the Art Designs and Optimizations
Safa Mohammed Sali, Mahmoud Meribout, Ashiyana Abdul Majeed
This paper presents a comprehensive review of recent advances in deploying convolutional neural networks (CNNs) for object detection, classification, and tracking on Field Programm…