語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Artificial Intelligence and Machine ...
~
SpringerLink (Online service)
Artificial Intelligence and Machine Learning for COVID-19
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Artificial Intelligence and Machine Learning for COVID-19/ edited by Fadi Al-Turjman.
其他作者:
Al-Turjman, Fadi.
面頁冊數:
X, 266 p. 105 illus., 91 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Health Promotion and Disease Prevention. -
電子資源:
https://doi.org/10.1007/978-3-030-60188-1
ISBN:
9783030601881
Artificial Intelligence and Machine Learning for COVID-19
Artificial Intelligence and Machine Learning for COVID-19
[electronic resource] /edited by Fadi Al-Turjman. - 1st ed. 2021. - X, 266 p. 105 illus., 91 illus. in color.online resource. - Studies in Computational Intelligence,9241860-9503 ;. - Studies in Computational Intelligence,564.
Smart Technologies for COVID-19: The Strategic Approaches in Combating the Virus -- A Review on COVID-19 -- Artificial Intelligence in the Face of the Corona Virus Pandemic -- Digital Transformation and Emerging Technologies for COVID-19 Pandemic: Social, Global and Industry Perspectives -- A Deep Analysis and Prediction of COVID-19 in India: Using Ensemble Regression Approach -- Image Enhancement in Healthcare Applications: A Review -- DEEP LEARNING APPROACH USING 3D-ImpCNN CLASSIFICATION FOR CORONAVIRUS DISEASE -- Drone-based Social Distancing, Sanitisation, Inspection, Monitoring and Control Room for COVID-19 -- Application of AI Techniques for COVID-19 in IoT and Big-Data Era: A Survey -- APPLICATION OF IoT, AI and 5G IN the FIGHT AGAINST the COVID-19 PENDAMIC -- AI techniques for Resource Management during Covid-19.
This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) – from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies. Includes advances related to COVID-19 diagnosis and tracking through artificial intelligence and machine learning; Enriches the fields of AI and ML with new and innovative operational ideas aimed at aiding in efforts to combat and track COVID-19; Pertains to researchers, scientists, engineers, and practitioners in the field of computing and smart cities technologies.
ISBN: 9783030601881
Standard No.: 10.1007/978-3-030-60188-1doiSubjects--Topical Terms:
593964
Health Promotion and Disease Prevention.
LC Class. No.: TK1-9971
Dewey Class. No.: 621.382
Artificial Intelligence and Machine Learning for COVID-19
LDR
:03861nam a22004095i 4500
001
1053560
003
DE-He213
005
20211014170305.0
007
cr nn 008mamaa
008
220103s2021 sz | s |||| 0|eng d
020
$a
9783030601881
$9
978-3-030-60188-1
024
7
$a
10.1007/978-3-030-60188-1
$2
doi
035
$a
978-3-030-60188-1
050
4
$a
TK1-9971
072
7
$a
TJK
$2
bicssc
072
7
$a
TEC041000
$2
bisacsh
072
7
$a
TJK
$2
thema
082
0 4
$a
621.382
$2
23
245
1 0
$a
Artificial Intelligence and Machine Learning for COVID-19
$h
[electronic resource] /
$c
edited by Fadi Al-Turjman.
250
$a
1st ed. 2021.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2021.
300
$a
X, 266 p. 105 illus., 91 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Studies in Computational Intelligence,
$x
1860-9503 ;
$v
924
505
0
$a
Smart Technologies for COVID-19: The Strategic Approaches in Combating the Virus -- A Review on COVID-19 -- Artificial Intelligence in the Face of the Corona Virus Pandemic -- Digital Transformation and Emerging Technologies for COVID-19 Pandemic: Social, Global and Industry Perspectives -- A Deep Analysis and Prediction of COVID-19 in India: Using Ensemble Regression Approach -- Image Enhancement in Healthcare Applications: A Review -- DEEP LEARNING APPROACH USING 3D-ImpCNN CLASSIFICATION FOR CORONAVIRUS DISEASE -- Drone-based Social Distancing, Sanitisation, Inspection, Monitoring and Control Room for COVID-19 -- Application of AI Techniques for COVID-19 in IoT and Big-Data Era: A Survey -- APPLICATION OF IoT, AI and 5G IN the FIGHT AGAINST the COVID-19 PENDAMIC -- AI techniques for Resource Management during Covid-19.
520
$a
This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) – from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies. Includes advances related to COVID-19 diagnosis and tracking through artificial intelligence and machine learning; Enriches the fields of AI and ML with new and innovative operational ideas aimed at aiding in efforts to combat and track COVID-19; Pertains to researchers, scientists, engineers, and practitioners in the field of computing and smart cities technologies.
650
2 4
$a
Health Promotion and Disease Prevention.
$3
593964
650
2 4
$a
Artificial Intelligence.
$3
646849
650
2 4
$a
Health Informatics.
$3
593963
650
1 4
$a
Communications Engineering, Networks.
$3
669809
650
0
$a
Health promotion.
$3
565089
650
0
$a
Artificial intelligence.
$3
559380
650
0
$a
Health informatics.
$3
1064466
650
0
$a
Electrical engineering.
$3
596380
700
1
$a
Al-Turjman, Fadi.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1168152
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783030601874
776
0 8
$i
Printed edition:
$z
9783030601898
776
0 8
$i
Printed edition:
$z
9783030601904
830
0
$a
Studies in Computational Intelligence,
$x
1860-949X ;
$v
564
$3
1253640
856
4 0
$u
https://doi.org/10.1007/978-3-030-60188-1
912
$a
ZDB-2-SCS
912
$a
ZDB-2-SXCS
950
$a
Computer Science (SpringerNature-11645)
950
$a
Computer Science (R0) (SpringerNature-43710)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入