6 citations · 10 across the 7 of their papers we have counts for
7 papers
EdgeNavMamba: Mamba Optimized Object Detection for Energy Efficient Edge Devices
Romina Aalishah, Mozhgan Navardi, Tinoosh Mohsenin
Deployment of efficient and accurate Deep Learning models has long been a challenge in autonomous navigation, particularly for real-time applications on resource-constrained edge d…
MedMambaLite: Hardware-Aware Mamba for Medical Image Classification
Romina Aalishah, Mozhgan Navardi, Tinoosh Mohsenin
AI-powered medical devices have driven the need for real-time, on-device inference such as biomedical image classification. Deployment of deep learning models at the edge is now us…
GenAI at the Edge: Comprehensive Survey on Empowering Edge Devices
Mozhgan Navardi, Romina Aalishah, Yuzhe Fu +4
Generative Artificial Intelligence (GenAI) applies models and algorithms such as Large Language Model (LLM) and Foundation Model (FM) to generate new data. GenAI, as a promising ap…
MambaLiteSR: Image Super-Resolution with Low-Rank Mamba using Knowledge Distillation
Romina Aalishah, Mozhgan Navardi, Tinoosh Mohsenin
Generative Artificial Intelligence (AI) has gained significant attention in recent years, revolutionizing various applications across industries. Among these, advanced vision model…
Energy-Aware FPGA Implementation of Spiking Neural Network with LIF Neurons
Asmer Hamid Ali, Mozhgan Navardi, Tinoosh Mohsenin
Tiny Machine Learning (TinyML) has become a growing field in on-device processing for Internet of Things (IoT) applications, capitalizing on AI algorithms that are optimized for th…
Squeezed Edge YOLO: Onboard Object Detection on Edge Devices
Edward Humes, Mozhgan Navardi, Tinoosh Mohsenin
Demand for efficient onboard object detection is increasing due to its key role in autonomous navigation. However, deploying object detection models such as YOLO on resource constr…
ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agents
Tejaswini Manjunath, Mozhgan Navardi, Prakhar Dixit +2
Robots have been successfully used to perform tasks with high precision. In real-world environments with sparse rewards and multiple goals, learning is still a major challenge and…