Research on Deep Learning Model of Fog Visibility Estimation Based on CNN

Junling Wang; Lijing Zhang

doi:10.1109/IMCEC51613.2021.9482258

Research on Deep Learning Model of Fog Visibility Estimation Based on CNN

Junling Wang, Lijing Zhang

安全科学与工程学院

Nanjing Tech University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

2 引用（Scopus）

摘要

Visibility prediction is an important subject of transportation safety research. At present, traditional sensing technology based on fog visibility prediction has problems such as large errors, high prices, and single-point monitoring defects. This article extracts airport video surveillance videos and extracts Frame extraction pictures, import the convolutional neural network deep learning model to identify the selected pictures, and evaluate the accuracy of the model, and its prediction accuracy meets the requirements of visibility prediction.

源语言	英语
主期刊名	IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference
编辑	Bing Xu
出版商	Institute of Electrical and Electronics Engineers Inc.
页	1355-1359
页数	5
ISBN（电子版）	9781728185347
DOI	https://doi.org/10.1109/IMCEC51613.2021.9482258
出版状态	已出版 - 18 6月 2021
活动	4th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021 - Chongqing, 中国期限: 18 6月 2021 → 20 6月 2021

出版系列

姓名	IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference
ISSN（印刷版）	2693-2814
ISSN（电子版）	2693-2776

会议

会议	4th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021
国家/地区	中国
市	Chongqing
时期	18/06/21 → 20/06/21

访问文件

10.1109/IMCEC51613.2021.9482258

其它文件与链接

链接到 Scopus 的出版物

引用此

Wang, J., & Zhang, L. (2021). Research on Deep Learning Model of Fog Visibility Estimation Based on CNN. 在 B. Xu (编辑), IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (页码 1355-1359). (IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IMCEC51613.2021.9482258

Wang, Junling ; Zhang, Lijing. / Research on Deep Learning Model of Fog Visibility Estimation Based on CNN. IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference. 编辑 / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2021. 页码 1355-1359 (IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference).

@inproceedings{1401a763972349f9903c9ae8d7eb5bff,

title = "Research on Deep Learning Model of Fog Visibility Estimation Based on CNN",

abstract = "Visibility prediction is an important subject of transportation safety research. At present, traditional sensing technology based on fog visibility prediction has problems such as large errors, high prices, and single-point monitoring defects. This article extracts airport video surveillance videos and extracts Frame extraction pictures, import the convolutional neural network deep learning model to identify the selected pictures, and evaluate the accuracy of the model, and its prediction accuracy meets the requirements of visibility prediction.",

keywords = "convolutional Neural Network, deep learning, frame draw, visibility forecast",

author = "Junling Wang and Lijing Zhang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 4th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021 ; Conference date: 18-06-2021 Through 20-06-2021",

year = "2021",

month = jun,

day = "18",

doi = "10.1109/IMCEC51613.2021.9482258",

language = "英语",

series = "IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1355--1359",

editor = "Bing Xu",

booktitle = "IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference",

address = "美国",

}

Wang, J & Zhang, L 2021, Research on Deep Learning Model of Fog Visibility Estimation Based on CNN. 在 B Xu (编辑), IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference. IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference, Institute of Electrical and Electronics Engineers Inc., 页码 1355-1359, 4th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021, Chongqing, 中国, 18/06/21. https://doi.org/10.1109/IMCEC51613.2021.9482258

Research on Deep Learning Model of Fog Visibility Estimation Based on CNN. / Wang, Junling; Zhang, Lijing.
IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference. 编辑 / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2021. 页码 1355-1359 (IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Research on Deep Learning Model of Fog Visibility Estimation Based on CNN

AU - Wang, Junling

AU - Zhang, Lijing

PY - 2021/6/18

Y1 - 2021/6/18

N2 - Visibility prediction is an important subject of transportation safety research. At present, traditional sensing technology based on fog visibility prediction has problems such as large errors, high prices, and single-point monitoring defects. This article extracts airport video surveillance videos and extracts Frame extraction pictures, import the convolutional neural network deep learning model to identify the selected pictures, and evaluate the accuracy of the model, and its prediction accuracy meets the requirements of visibility prediction.

AB - Visibility prediction is an important subject of transportation safety research. At present, traditional sensing technology based on fog visibility prediction has problems such as large errors, high prices, and single-point monitoring defects. This article extracts airport video surveillance videos and extracts Frame extraction pictures, import the convolutional neural network deep learning model to identify the selected pictures, and evaluate the accuracy of the model, and its prediction accuracy meets the requirements of visibility prediction.

KW - convolutional Neural Network

KW - deep learning

KW - frame draw

KW - visibility forecast

UR - http://www.scopus.com/inward/record.url?scp=85116129431&partnerID=8YFLogxK

U2 - 10.1109/IMCEC51613.2021.9482258

DO - 10.1109/IMCEC51613.2021.9482258

M3 - 会议稿件

AN - SCOPUS:85116129431

T3 - IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference

SP - 1355

EP - 1359

BT - IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference

A2 - Xu, Bing

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 4th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021

Y2 - 18 June 2021 through 20 June 2021

ER -

Wang J, Zhang L. Research on Deep Learning Model of Fog Visibility Estimation Based on CNN. 在 Xu B, 编辑, IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference. Institute of Electrical and Electronics Engineers Inc. 2021. 页码 1355-1359. (IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference). doi: 10.1109/IMCEC51613.2021.9482258

Research on Deep Learning Model of Fog Visibility Estimation Based on CNN

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