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Images as Data for Social Science Research : An Introduction to Convolutional Neural Nets for Image Classification

By: (Author) Andreu Casas , (Author) John D. Wilkerson , (Author) Nora Webb Williams

Manufacture on Demand

Ksh 3,250.00

Format: Paperback / Softback

ISBN-10: 1108816851

ISBN-13: 9781108816854

Series: Elements in Quantitative and Computational Methods for the Social Sciences

Publisher: Cambridge University Press

Imprint: Cambridge University Press

Country of Manufacture: US

Country of Publication: GB

Publication Date: Aug 13th, 2020

Print length: 75 Pages

Weight: 142 grams

Dimensions (height x width x thickness): 15.20 x 22.80 x 0.80 cms

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Shows how innovation in computer vision methods can markedly lower the costs of using images as data. Introduces readers to deep learning algorithms commonly used for object recognition, facial recognition, and visual sentiment analysis. Provides guidance and instruction for scholars interested in using these methods in their own research.
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.

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