大葉大學圖書館 |

Images as data for social science research[electronic resource] :an introduction to convolutional neural nets for image classification /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	320.072
書名/作者:	Images as data for social science research : an introduction to convolutional neural nets for image classification // Nora Webb Williams, Andreu Casas, John D. Wilkerson.
作者:	Webb Williams, Nora.
其他作者:	Casas, Andreu.
出版者:	Cambridge : : Cambridge University Press,, 2020.
面頁冊數:	78 p. : : ill. (some col.), digital ; ; 23 cm.
附註:	Title from publisher's bibliographic system (viewed on 17 Jul 2020).
標題:	Political science - Research
標題:	Image processing - Digital techniques.
標題:	Machine learning.
標題:	Neural networks (Computer science)
ISBN:	9781108860741
ISBN:	9781108816854
摘要、提要註:	Images play a crucial role in shaping and reflecting political life. Digitization has vastly increased the presence of such images in daily life, creating valuable new research opportunities for social scientists. We show how recent innovations in computer vision methods can substantially lower the costs of using images as data. We introduce readers to the deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. We then provide guidance and specific instructions for scholars interested in using these methods in their own research.
電子資源:	https://doi.org/10.1017/9781108860741

Images as data for social science research[electronic resource] :an introduction to convolutional neural nets for image classification /
Webb Williams, Nora.

Images as data for social science researchan introduction to convolutional neural nets for image classification /[electronic resource] :Nora Webb Williams, Andreu Casas, John D. Wilkerson. - Cambridge :Cambridge University Press,2020. - 78 p. :ill. (some col.), digital ; 23 cm. - Cambridge elements. Elements in quantitative and computational methods for social science. - Cambridge elements.Elements in quantitative and computational methods for social science..

Title from publisher's bibliographic system (viewed on 17 Jul 2020).

Images play a crucial role in shaping and reflecting political life. Digitization has vastly increased the presence of such images in daily life, creating valuable new research opportunities for social scientists. We show how recent innovations in computer vision methods can substantially lower the costs of using images as data. We introduce readers to the deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. We then provide guidance and specific instructions for scholars interested in using these methods in their own research.

ISBN: 9781108860741Subjects--Topical Terms:

477389
Political science
--Research

LC Class. No.: JA86 / .W55 2020

Dewey Class. No.: 320.072

Images as data for social science research[electronic resource] :an introduction to convolutional neural nets for image classification /
LDR:01604nmm a2200253 a 4500 001 522803
003 UkCbUP
005 20200809171940.0
006 m d
007 cr nn 008maaau
008 230416s2020 enk o 1 0 eng d
020 $a 9781108860741 $q (electronic bk.)
020 $a 9781108816854 $q (paperback)
035 $a CR9781108860741
040 $a UkCbUP $b eng $c UkCbUP $d GP
050 4 $a JA86 $b .W55 2020
082 0 4 $a 320.072 $2 23
090 $a JA86 $b .W368 2020
100 1 $a Webb Williams, Nora. $3 748139
245 1 0 $a Images as data for social science research $h [electronic resource] : $b an introduction to convolutional neural nets for image classification / $c Nora Webb Williams, Andreu Casas, John D. Wilkerson.
260 $a Cambridge : $b Cambridge University Press, $c 2020.
300 $a 78 p. : $b ill. (some col.), digital ; $c 23 cm.
490 1 $a Cambridge elements. Elements in quantitative and computational methods for social science
500 $a Title from publisher's bibliographic system (viewed on 17 Jul 2020).
520 $a Images play a crucial role in shaping and reflecting political life. Digitization has vastly increased the presence of such images in daily life, creating valuable new research opportunities for social scientists. We show how recent innovations in computer vision methods can substantially lower the costs of using images as data. We introduce readers to the deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. We then provide guidance and specific instructions for scholars interested in using these methods in their own research.
650 0 $a Political science $x Research $x Methodology. $3 477389
650 0 $a Image processing $x Digital techniques. $3 365611
650 0 $a Machine learning. $3 202931
650 0 $a Neural networks (Computer science) $3 386157
700 1 $a Casas, Andreu. $3 748140
700 1 $a Wilkerson, John D. $3 748141
830 0 $a Cambridge elements. $p Elements in quantitative and computational methods for social science. $3 748142
856 4 0 $u https://doi.org/10.1017/9781108860741