TY - JOUR
T1 - Powering Visualization with Deep Learning
AU - Wu, Yingcai
AU - Fu, Siwei
AU - Zhao, Jian
AU - Bryan, Chris
N1 - Publisher Copyright:
© 1981-2012 IEEE.
PY - 2021/9/1
Y1 - 2021/9/1
N2 - The articles in this Special Issue focus on the application of deep learning techniques in visualization. The great success of deep learning techniques in computer vision, natural language processing, and speech recognition offers new opportunities for data visualization and analytics. We can leverage these technologies not only to recognize visual representations but also to understand analytical tasks. However, introducing deep learning techniques into visualization tasks faces new challenges and problems to solve. In this issue, we present six articles that illustrate how deep learning techniques interact with visualization.
AB - The articles in this Special Issue focus on the application of deep learning techniques in visualization. The great success of deep learning techniques in computer vision, natural language processing, and speech recognition offers new opportunities for data visualization and analytics. We can leverage these technologies not only to recognize visual representations but also to understand analytical tasks. However, introducing deep learning techniques into visualization tasks faces new challenges and problems to solve. In this issue, we present six articles that illustrate how deep learning techniques interact with visualization.
UR - http://www.scopus.com/inward/record.url?scp=85114714281&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85114714281&partnerID=8YFLogxK
U2 - 10.1109/MCG.2021.3102711
DO - 10.1109/MCG.2021.3102711
M3 - Review article
AN - SCOPUS:85114714281
SN - 0272-1716
VL - 41
SP - 16
EP - 17
JO - IEEE Computer Graphics and Applications
JF - IEEE Computer Graphics and Applications
IS - 5
M1 - 9535171
ER -