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Editorial: Introduction to the Special Issue on Deep Learning for High-Dimensional Sensing
被引:1
|作者:
YUAN, X. I. N.
[1
]
BRADY, D. A. V. I. D. J.
[2
]
SUO, J. I. N. L. I.
[3
]
ARGUELLO, H. E. N. R. Y.
[4
]
RODRIGUES, M. I. G. U. E. L.
[5
]
KATSAGGELOS, A. G. G. E. L. O. S. K.
[6
]
机构:
[1] Westlake Univ, Sch Engn, Hangzhou 310030, Zhejiang, Peoples R China
[2] Univ Arizona, Coll Opt Sci, Tucson, AZ 85719 USA
[3] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[4] Univ Ind Santander, Dept Syst Engn & Informat, Bucaramanga 680002, Colombia
[5] UCL, Dept Elect & Elect Engn, London WC1E 7JE, England
[6] Northwestern Univ, Dept Elect & Comp Engn, Evanston, IL 60208 USA
关键词:
Special issues and sections;
Deep learning;
Robot sensing systems;
Surveillance;
Signal processing;
Machine vision;
Computer vision;
Artificial intelligence;
Sensors;
D O I:
10.1109/JSTSP.2022.3185190
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
The papers in this special section focus on deep learning for high-dimensional sensing. People live in a high-dimensional world and sensing is the first step to perceive and understand the environment for both human beings and machines. Therefore, high-dimensional sensing (HDS) plays a pivotal role in many fields such as robotics, signal processing, computer vision and surveillance. The recent explosive growth of artificial intelligence has provided new opportunities and tools for HDS, especially for machine vision. In many emerging real applications such as advanced driver assistance systems/autonomous driving systems, large-scale, high-dimensional and diverse types of data need to be captured and processed with high accuracy and in a real-time manner. Bearing this in mind, now is the time to develop new sensing and processing techniques with high performance to capture high-dimensional data by leveraging recent advances in deep learning (DL).
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页码:603 / 607
页数:5
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