activity
20222024
most citedLarge Scale Foundation Models for Intelligent Manufacturing Applications: A Survey

6 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

Leveraging Foundation Model Automatic Data Augmentation Strategies and Skeletal Points for Hands Action Recognition in Industrial Assembly Lines

Liang Wu, X. -G. Ma

On modern industrial assembly lines, many intelligent algorithms have been developed to replace or supervise workers. However, we found that there were bottlenecks in both training…

cs.AI2023★ 6 cited

Large Scale Foundation Models for Intelligent Manufacturing Applications: A Survey

Haotian Zhang, Semujju Stuart Dereck, Zhicheng Wang +9

Although the applications of artificial intelligence especially deep learning had greatly improved various aspects of intelligent manufacturing, they still face challenges for wide…

cs.CV2023

LSGDDN-LCD: An Appearance-based Loop Closure Detection using Local Superpixel Grid Descriptors and Incremental Dynamic Nodes

Baosheng Zhang

Loop Closure Detection (LCD) is an essential component of visual simultaneous localization and mapping (SLAM) systems. It enables the recognition of previously visited scenes to el…

cs.AI2023★ 1 cited

Large-Scale Traffic Signal Control Using Constrained Network Partition and Adaptive Deep Reinforcement Learning

Hankang Gu, Shangbo Wang, Xiaoguang Ma +4

Multi-agent Deep Reinforcement Learning (MADRL) based traffic signal control becomes a popular research topic in recent years. To alleviate the scalability issue of completely cent…

cs.GT2023

Large-Scale Traffic Signal Control by a Nash Deep Q-network Approach

Yuli. Zhang, Shangbo. Wang, Ruiyuan. Jiang

Reinforcement Learning (RL) is currently one of the most commonly used techniques for traffic signal control (TSC), which can adaptively adjusted traffic signal phase and duration…

cs.CV2022

DynPL-SVO: A Robust Stereo Visual Odometry for Dynamic Scenes

Baosheng Zhang, Xiaoguang Ma, Hongjun Ma +1

Most feature-based stereo visual odometry (SVO) approaches estimate the motion of mobile robots by matching and tracking point features along a sequence of stereo images. However,…