most citedImportance-Aware Image Segmentation-based Semantic Communication for Autonomous Driving

2 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20242 cited

Consistency Flow Matching: Defining Straight Flows with Velocity Consistency

Ling Yang, Zixiang Zhang, Zhilong Zhang +6

Flow matching (FM) is a general framework for defining probability paths via Ordinary Differential Equations (ODEs) to transform between noise and data samples. Recent approaches a…

cs.LG2024

Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning

Xu-Hui Liu, Tian-Shuo Liu, Shengyi Jiang +4

Combining offline and online reinforcement learning (RL) techniques is indeed crucial for achieving efficient and safe learning where data acquisition is expensive. Existing method…

cs.CV2024

Structure-Guided Adversarial Training of Diffusion Models

Ling Yang, Haotian Qian, Zhilong Zhang +2

Diffusion models have demonstrated exceptional efficacy in various generative applications. While existing models focus on minimizing a weighted sum of denoising score matching los…

cs.NI20242 cited

Importance-Aware Image Segmentation-based Semantic Communication for Autonomous Driving

Jie Lv, Haonan Tong, Qiang Pan +4

This article studies the problem of image segmentation-based semantic communication in autonomous driving. In real traffic scenes, detecting the key objects (e.g., vehicles, pedest…

cs.LG20231 cited

Identifying Subgroups of ICU Patients Using End-to-End Multivariate Time-Series Clustering Algorithm Based on Real-World Vital Signs Data

Tongyue Shi, Zhilong Zhang, Wentie Liu +5

This study employed the MIMIC-IV database as data source to investigate the use of dynamic, high-frequency, multivariate time-series vital signs data, including temperature, heart…