most citedThe Streetscape Application Services Stack (SASS): Towards a Distributed Sensing Architecture for Urban Applications

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV2024

A dual contrastive framework

Yuan Sun, Zhao Zhang, Jorge Ortiz

In current multimodal tasks, models typically freeze the encoder and decoder while adapting intermediate layers to task-specific goals, such as region captioning. Region-level visu…

cs.NI20241 cited

The Streetscape Application Services Stack (SASS): Towards a Distributed Sensing Architecture for Urban Applications

Navid Salami Pargoo, Mahshid Ghasemi, Shuren Xia +8

As urban populations grow, cities are becoming more complex, driving the deployment of interconnected sensing systems to realize the vision of smart cities. These systems aim to im…

cs.HC2024

An AI-Based System Utilizing IoT-Enabled Ambient Sensors and LLMs for Complex Activity Tracking

Yuan Sun, Jorge Ortiz

Complex activity recognition plays an important role in elderly care assistance. However, the reasoning ability of edge devices is constrained by the classic machine learning model…

cs.LG2024

Rapid Review of Generative AI in Smart Medical Applications

Yuan Sun, Jorge Ortiz

With the continuous advancement of technology, artificial intelligence has significantly impacted various fields, particularly healthcare. Generative models, a key AI technology, h…

cs.AI2024

Optimizing Autonomous Driving for Safety: A Human-Centric Approach with LLM-Enhanced RLHF

Yuan Sun, Navid Salami Pargoo, Peter J. Jin +1

Reinforcement Learning from Human Feedback (RLHF) is popular in large language models (LLMs), whereas traditional Reinforcement Learning (RL) often falls short. Current autonomous…