Phoenixmap: Spatio-Temporal Distribution Analysis With Deep Learning Classifications

机译：PhoenixMap：时空分布分析，深度学习分类

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In this paper, we introduce PhoenixMap, a visual analytics system to help analysts understand spatiotemporal distribution patterns and anomalies of many objects. It focuses on solving two VA challenges. First, visualizing the spatial distribution of many points under different categories especially when these points partially overlap with each other; Second, employing visual means to classify bird calls using deep learning CNN method. This PhoenixMap system can successfully help us understand the change and patterns of birds regions over many years.

机译：在本文中，我们介绍了PhoenixMap，一种视觉分析系统，帮助分析师了解许多物体的时空分布模式和异常。它侧重于解决两个va挑战。首先，在不同类别下可视化许多点的空间分布，特别是当这些点彼此部分地重叠时;其次，采用视觉手段使用深度学习CNN方法对鸟呼叫进行分类。这款凤凰表MAP系统可以成功帮助我们多年来了解鸟类地区的变化和模式。

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《IEEE Conference on Visual Analytics Science anf Technology》|2018年|130 p. :|共2页
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作者
Junhan Zhao; xiang Liu; Ryan Guan; Josephine Zhang; Baijian Yang; Zhenyu Qian; Yingjie Chen;
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中图分类 TP391.77;
关键词
Human-centered computing; Visualization; Visualization design and evaluation methods;

机译：以人为本的计算;可视化;可视化设计和评估方法;

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4. Phoenixmap: Spatio-Temporal Distribution Analysis With Deep Learning Classifications [C] . Junhan Zhao, xiang Liu, Ryan Guan, IEEE Conference on Visual Analytics Science anf Technology . 2018

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Phoenixmap: Spatio-Temporal Distribution Analysis With Deep Learning Classifications

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