語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Challenges and trends in multimodal ...
~
Ponce, Hiram.
FindBook
Google Book
Amazon
博客來
Challenges and trends in multimodal fall detection for healthcare
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Challenges and trends in multimodal fall detection for healthcare/ edited by Hiram Ponce ... [et al.].
其他作者:
Ponce, Hiram.
出版者:
Cham :Springer International Publishing : : 2020.,
面頁冊數:
xiii, 259 p. :ill., digital ;24 cm.
內容註:
Challenges and Solutions on Human Fall Detection and Classification -- Open Source Implementation for Fall Classification and Fall Detection Systems -- Detecting Human Activities based on a Multimodal Sensor Data Set using a Bidirectional Long Short-Term Memory Model: A Case Study -- Approaching Fall Classification using the UP-Fall Detection Dataset: Analysis and Results from an International Competition -- Reviews and Trends on Multimodal Healthcare -- A Novel Approach for Human Fall Detection and Fall Risk Assessment.
Contained By:
Springer eBooks
標題:
Biosensors. -
電子資源:
https://doi.org/10.1007/978-3-030-38748-8
ISBN:
9783030387488
Challenges and trends in multimodal fall detection for healthcare
Challenges and trends in multimodal fall detection for healthcare
[electronic resource] /edited by Hiram Ponce ... [et al.]. - Cham :Springer International Publishing :2020. - xiii, 259 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.2732198-4182 ;. - Studies in systems, decision and control ;v.273..
Challenges and Solutions on Human Fall Detection and Classification -- Open Source Implementation for Fall Classification and Fall Detection Systems -- Detecting Human Activities based on a Multimodal Sensor Data Set using a Bidirectional Long Short-Term Memory Model: A Case Study -- Approaching Fall Classification using the UP-Fall Detection Dataset: Analysis and Results from an International Competition -- Reviews and Trends on Multimodal Healthcare -- A Novel Approach for Human Fall Detection and Fall Risk Assessment.
This book focuses on novel implementations of sensor technologies, artificial intelligence, machine learning, computer vision and statistics for automated, human fall recognition systems and related topics using data fusion. It includes theory and coding implementations to help readers quickly grasp the concepts and to highlight the applicability of this technology. For convenience, it is divided into two parts. The first part reviews the state of the art in human fall and activity recognition systems, while the second part describes a public dataset especially curated for multimodal fall detection. It also gathers contributions demonstrating the use of this dataset and showing examples. This book is useful for anyone who is interested in fall detection systems, as well as for those interested in solving challenging, signal recognition, vision and machine learning problems. Potential applications include health care, robotics, sports, human-machine interaction, among others.
ISBN: 9783030387488
Standard No.: 10.1007/978-3-030-38748-8doiSubjects--Topical Terms:
621001
Biosensors.
LC Class. No.: R857.B54 / C435 2020
Dewey Class. No.: 610.285
Challenges and trends in multimodal fall detection for healthcare
LDR
:02583nmm a2200337 a 4500
001
2215672
003
DE-He213
005
20200620143834.0
006
m d
007
cr nn 008maaau
008
201120s2020 sz s 0 eng d
020
$a
9783030387488
$q
(electronic bk.)
020
$a
9783030387471
$q
(paper)
024
7
$a
10.1007/978-3-030-38748-8
$2
doi
035
$a
978-3-030-38748-8
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
R857.B54
$b
C435 2020
072
7
$a
MQW
$2
bicssc
072
7
$a
TEC059000
$2
bisacsh
072
7
$a
MQW
$2
thema
082
0 4
$a
610.285
$2
23
090
$a
R857.B54
$b
C437 2020
245
0 0
$a
Challenges and trends in multimodal fall detection for healthcare
$h
[electronic resource] /
$c
edited by Hiram Ponce ... [et al.].
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2020.
300
$a
xiii, 259 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Studies in systems, decision and control,
$x
2198-4182 ;
$v
v.273
505
0
$a
Challenges and Solutions on Human Fall Detection and Classification -- Open Source Implementation for Fall Classification and Fall Detection Systems -- Detecting Human Activities based on a Multimodal Sensor Data Set using a Bidirectional Long Short-Term Memory Model: A Case Study -- Approaching Fall Classification using the UP-Fall Detection Dataset: Analysis and Results from an International Competition -- Reviews and Trends on Multimodal Healthcare -- A Novel Approach for Human Fall Detection and Fall Risk Assessment.
520
$a
This book focuses on novel implementations of sensor technologies, artificial intelligence, machine learning, computer vision and statistics for automated, human fall recognition systems and related topics using data fusion. It includes theory and coding implementations to help readers quickly grasp the concepts and to highlight the applicability of this technology. For convenience, it is divided into two parts. The first part reviews the state of the art in human fall and activity recognition systems, while the second part describes a public dataset especially curated for multimodal fall detection. It also gathers contributions demonstrating the use of this dataset and showing examples. This book is useful for anyone who is interested in fall detection systems, as well as for those interested in solving challenging, signal recognition, vision and machine learning problems. Potential applications include health care, robotics, sports, human-machine interaction, among others.
650
0
$a
Biosensors.
$3
621001
650
0
$a
Falls (Accidents) in old age.
$3
2203691
650
1 4
$a
Biomedical Engineering and Bioengineering.
$3
3381533
650
2 4
$a
Computational Intelligence.
$3
1001631
650
2 4
$a
Biomechanics.
$3
548685
700
1
$a
Ponce, Hiram.
$3
3447382
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
830
0
$a
Studies in systems, decision and control ;
$v
v.273.
$3
3447383
856
4 0
$u
https://doi.org/10.1007/978-3-030-38748-8
950
$a
Engineering (Springer-11647)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9390576
電子資源
11.線上閱覽_V
電子書
EB R857.B54 C435 2020
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入