.png){kind=icon}
返回
AI-based computer vision using deep learning in 6G wireless networks
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compeleceng.2022.108233.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Modern businesses benefit significantly from advances in computer vision technology, one of the important sectors of artificially intelligent and computer science research. Advanced computer vision issues like image processing, object recognition, and biometric authentication can benefit from using deep learning methods. As smart devices and facilities advance rapidly, current net-works such as 4 G and the forthcoming 5 G networks may not adapt to the rapidly increasing demand. Classification of images, object classification, and facial recognition software are some of the most difficult computer vision problems that can be solved using deep learning methods. As a new paradigm for 6Core network design and analysis, artificial intelligence (AI) has recently been used. Therefore, in this paper, the 6 G wireless network is used along with Deep Learning to solve the above challenges by introducing a new methodology named Optimizing Computer Vision with AI-enabled technology (OCV-AI). This research uses deep learning - efficiency al-gorithms (DL-EA) for computer vision to address the issues mentioned and improve the system's outcome. Therefore, deep learning 6 G proposed frameworks (Dl-6 G) are suggested in this paper to recognize pattern recognition and intelligent management systems and provide driven meth-odology planned to be provisioned automatically. For Advanced analytics wise, 6 G networks can summarize the significant areas for future research and potential solutions, including image enhancement, machine vision, and access control.
Keyword:
6G
Wireless communication
AI
Machine learning
Deep learning
Mobile communication
期刊
C
IF:
4.9
论文数:
6.7K
被引数:
1.3W
机构
引用论文
A framework of human action recognition using length control features fusion and weighted entropy-variances based feature selection基于长度控制特征融合和基于加权熵方差的特征选择的人体动作识别框架
PREAI
分享收藏
Prediction of pork loin quality using online computer vision system and artificial intelligence model.png)
MEAT SCIENCE
MEAT SCIENCEIF6.1
PREAI
分享收藏
查看更多内容