Search Results for author:
Found 6 papers, 3 papers with code
NeurIT: Pushing the Limit of Neural Inertial Tracking for Indoor Robotic IoT
To enhance the tracking accuracy for indoor robotic applications, we introduce NeurIT, a sequence-to-sequence framework that elevates tracking accuracy to a new level.
Are You Being Tracked? Discover the Power of Zero-Shot Trajectory Tracing with LLMs!
There is a burgeoning discussion around the capabilities of Large Language Models (LLMs) in acting as fundamental components that can be seamlessly incorporated into Artificial Intelligence of Things (AIoT) to interpret complex trajectories.
HARGPT: Are LLMs Zero-Shot Human Activity Recognizers?
Our study, HARGPT, presents an affirmative answer by demonstrating that LLMs can comprehend raw IMU data and perform HAR tasks in a zero-shot manner, with only appropriate prompts.
Robust Target Detection of Intelligent Integrated Optical Camera and mmWave Radar System
To improve the target detection performance under complex real-world scenarios, this paper proposes an intelligent integrated optical camera and millimeter-wave (mmWave) radar system.
Enhancing Deep Learning Performance of Massive MIMO CSI Feedback
In this paper, we propose a jigsaw puzzles aided training strategy (JPTS) to enhance the deep learning-based Massive MIMO CSI feedback approaches by maximizing mutual information between the original CSI and the compressed CSI.
CLNet: Complex Input Lightweight Neural Network designed for Massive MIMO CSI Feedback
Numerous deep learning for massive MIMO CSI feedback approaches have demonstrated their efficiency and potential.
