Deep Learning in Biological Image and Signal Processing

被引:3
|
作者
Meijering, Erik [1 ]
Calhoun, Vince D. [2 ,3 ,4 ]
Menegaz, Gloria [5 ]
Miller, David J. [6 ]
Ye, Jong Chul [7 ,8 ,9 ]
机构
[1] Univ New South Wales, Sch Comp Sci & Engn, Biomed Image Comp, Sydney, NSW 2052, Australia
[2] Triinst Ctr Translat Res Neuroimaging & Data Sci, Atlanta, GA 30303 USA
[3] Georgia Inst Technol, Atlanta, GA 30332 USA
[4] Emory Univ, Atlanta, GA 30322 USA
[5] Univ Verona, Dept Comp Sci, Bioengn, I-37134 Verona, Italy
[6] Penn State Univ, Sch Elect Engn & Comp Sci, State Coll, PA 16802 USA
[7] Korea Adv Inst Sci & Technol, Dept Bio Brain Engn, Daejeon 34141, South Korea
[8] Korea Adv Inst Sci & Technol, Dept Math Sci, Daejeon 34141, South Korea
[9] Korea Adv Inst Sci & Technol, Grad Sch Artificial Intelligence, Daejeon 34141, South Korea
关键词
Deep learning;
D O I
10.1109/MSP.2021.3134525
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
Biological research on the fundamental structural and functional properties of life - from molecules to cells, tissues, organs, and complete organisms, including human life - relies heavily on advanced imaging systems and measurement devices generating data of ever-increasing quantity and complexity. Automated processing and analysis of these data through increasingly sophisticated computational methods have become indispensable in exploiting relevant information and enabling researchers to detect patterns that may be unnoticeable to human senses. © 1991-2012 IEEE.
引用
收藏
页码:24 / 26
页数:3
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