A Generative Approach to Visualizing Satellite Data

被引：2

作者：

Mitra, Saptashwa ^{[1
]}

Rammer, Daniel ^{[1
]}

Pallickara, Shrideep ^{[1
]}

Pallickara, Sangmi Lee ^{[1
]}

机构：

[1] Colorado State Univ, Dept Comp Sci, Ft Collins, CO 80523 USA

来源：

2021 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER 2021) | 2021年

基金：

美国国家科学基金会;

关键词：

super-resolution; generative adversarial networks; in-memory storage; visual analytics;

D O I：

10.1109/Cluster48925.2021.00079

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose EVOKE, a model based on progressive Generative Adversarial Networks, that dynamically reconstructs high-resolution imagery during zoom-in operations using in-memory historical low-resolution images and is space-efficient to facilitate memory-residency at the clients.

引用

页码：815 / 816

页数：2

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