18 citations · 74 across the 36 of their papers we have counts for
10 papers · 1 filter
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…
Multi-RAG: A Multimodal Retrieval-Augmented Generation System for Adaptive Video Understanding
Mingyang Mao, Mariela M. Perez-Cabarcas, Utteja Kallakuri +3
To effectively engage in human society, the ability to adapt, filter information, and make informed decisions in ever-changing situations is critical. As robots and intelligent age…
EDEN: Entorhinal Driven Egocentric Navigation Toward Robotic Deployment
Mikolaj Walczak, Romina Aalishah, Wyatt Mackey +5
Deep reinforcement learning agents are often fragile while humans remain adaptive and flexible to varying scenarios. To bridge this gap, we present EDEN, a biologically inspired na…
Enabling On-Device Medical AI Assistants via Input-Driven Saliency Adaptation
Uttej Kallakurik, Edward Humes, Rithvik Jonna +2
Large Language Models (LLMs) have significant impact on the healthcare scenarios but remain prohibitively large for deployment in real-time, resource-constrained environments such…
RAFT -- A Domain Adaptation Framework for RGB & LiDAR Semantic Segmentation
Edward Humes, Xiaomin Lin, Boxun Hu +2
Image segmentation is a powerful computer vision technique for scene understanding. However, real-world deployment is stymied by the need for high-quality, meticulously labeled dat…
ATLASv2: LLM-Guided Adaptive Landmark Acquisition and Navigation on the Edge
Mikolaj Walczak, Uttej Kallakuri, Tinoosh Mohsenin
Autonomous systems deployed on edge devices face significant challenges, including resource constraints, real-time processing demands, and adapting to dynamic environments. This wo…
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…
Decentralised Resource Sharing in TinyML: Wireless Bilayer Gossip Parallel SGD for Collaborative Learning
Ziyuan Bao, Eiman Kanjo, Soumya Banerjee +2
With the growing computational capabilities of microcontroller units (MCUs), edge devices can now support machine learning models. However, deploying decentralised federated learni…