LSTM and ResNets Deep Learning Aided End-to-End Intelligent Communication Systems

Haotian Zhang; Lin Zhang; Yuan Jiang; Zhiqiang Wu

doi:10.1109/ICTC51749.2021.9441657

LSTM and ResNets Deep Learning Aided End-to-End Intelligent Communication Systems

Haotian Zhang, Lin Zhang, Yuan Jiang, Zhiqiang Wu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	2021 2nd Information Communication Technologies Conference, ICTC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	156-160
Number of pages	5
ISBN (Electronic)	9780738142876
DOIs	https://doi.org/10.1109/ICTC51749.2021.9441657
State	Published - May 7 2021
Externally published	Yes
Event	2nd Information Communication Technologies Conference, ICTC 2021 - Nanjing, China Duration: May 7 2021 → May 9 2021

Publication series

Name	2021 2nd Information Communication Technologies Conference, ICTC 2021

Conference

Conference	2nd Information Communication Technologies Conference, ICTC 2021
Country/Territory	China
City	Nanjing
Period	5/7/21 → 5/9/21

ASJC Scopus Subject Areas

Signal Processing
Computer Networks and Communications
Hardware and Architecture
Software

Keywords

Deep learning
Intelligent auto-transmission
Long short-term memory (LSTM)
Neural network architecture
Residual networks (ResNets)

Access to Document

10.1109/ICTC51749.2021.9441657

Cite this

Zhang, H., Zhang, L., Jiang, Y., & Wu, Z. (2021). LSTM and ResNets Deep Learning Aided End-to-End Intelligent Communication Systems. In 2021 2nd Information Communication Technologies Conference, ICTC 2021 (pp. 156-160). Article 9441657 (2021 2nd Information Communication Technologies Conference, ICTC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICTC51749.2021.9441657

LSTM and ResNets Deep Learning Aided End-to-End Intelligent Communication Systems. / Zhang, Haotian; Zhang, Lin; Jiang, Yuan et al.
2021 2nd Information Communication Technologies Conference, ICTC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 156-160 9441657 (2021 2nd Information Communication Technologies Conference, ICTC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhang, H, Zhang, L, Jiang, Y & Wu, Z 2021, LSTM and ResNets Deep Learning Aided End-to-End Intelligent Communication Systems. in 2021 2nd Information Communication Technologies Conference, ICTC 2021., 9441657, 2021 2nd Information Communication Technologies Conference, ICTC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 156-160, 2nd Information Communication Technologies Conference, ICTC 2021, Nanjing, China, 5/7/21. https://doi.org/10.1109/ICTC51749.2021.9441657

Zhang H, Zhang L, Jiang Y, Wu Z. LSTM and ResNets Deep Learning Aided End-to-End Intelligent Communication Systems. In 2021 2nd Information Communication Technologies Conference, ICTC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 156-160. 9441657. (2021 2nd Information Communication Technologies Conference, ICTC 2021). doi: 10.1109/ICTC51749.2021.9441657

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title = "LSTM and ResNets Deep Learning Aided End-to-End Intelligent Communication Systems",

keywords = "Deep learning, Intelligent auto-transmission, Long short-term memory (LSTM), Neural network architecture, Residual networks (ResNets)",

author = "Haotian Zhang and Lin Zhang and Yuan Jiang and Zhiqiang Wu",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2nd Information Communication Technologies Conference, ICTC 2021 ; Conference date: 07-05-2021 Through 09-05-2021",

year = "2021",

month = may,

day = "7",

doi = "10.1109/ICTC51749.2021.9441657",

language = "English",

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T1 - LSTM and ResNets Deep Learning Aided End-to-End Intelligent Communication Systems

AU - Zhang, Haotian

AU - Zhang, Lin

AU - Jiang, Yuan

AU - Wu, Zhiqiang

PY - 2021/5/7

Y1 - 2021/5/7

KW - Deep learning

KW - Intelligent auto-transmission

KW - Long short-term memory (LSTM)

KW - Neural network architecture

KW - Residual networks (ResNets)

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U2 - 10.1109/ICTC51749.2021.9441657

DO - 10.1109/ICTC51749.2021.9441657

M3 - Conference contribution

AN - SCOPUS:85107800705

T3 - 2021 2nd Information Communication Technologies Conference, ICTC 2021

SP - 156

EP - 160

BT - 2021 2nd Information Communication Technologies Conference, ICTC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd Information Communication Technologies Conference, ICTC 2021

Y2 - 7 May 2021 through 9 May 2021

ER -

LSTM and ResNets Deep Learning Aided End-to-End Intelligent Communication Systems

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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Cite this