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In Search of Basement Indicators from Street View Imagery Data: An Investigation of Data Sources and Analysis Strategies. 从街景图像数据中寻找地下室指标:数据来源调查和分析策略。
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-01-01 Epub Date: 2023-01-20 DOI: 10.1007/s13218-022-00792-4
Anh Vu Vo, Michela Bertolotto, Ulrich Ofterdinger, Debra F Laefer

Street view imagery databases such as Google Street View, Mapillary, and Karta View provide great spatial and temporal coverage for many cities globally. Those data, when coupled with appropriate computer vision algorithms, can provide an effective means to analyse aspects of the urban environment at scale. As an effort to enhance current practices in urban flood risk assessment, this project investigates a potential use of street view imagery data to identify building features that indicate buildings' vulnerability to flooding (e.g., basements and semi-basements). In particular, this paper discusses (1) building features indicating the presence of basement structures, (2) available imagery data sources capturing those features, and (3) computer vision algorithms capable of automatically detecting the features of interest. The paper also reviews existing methods for reconstructing geometry representations of the extracted features from images and potential approaches to account for data quality issues. Preliminary experiments were conducted, which confirmed the usability of the freely available Mapillary images for detecting basement railings as an example type of basement features, as well as geolocating the features.

谷歌街景、Mapillary和Karta view等街景图像数据库为全球许多城市提供了良好的空间和时间覆盖。这些数据与适当的计算机视觉算法相结合,可以提供一种有效的手段来大规模分析城市环境的各个方面。为了加强城市洪水风险评估的现行做法,该项目调查了街景图像数据的潜在用途,以确定表明建筑物易受洪水影响的建筑特征(例如地下室和半地下室)。特别地,本文讨论了(1)指示地下室结构存在的建筑特征,(2)捕捉这些特征的可用图像数据源,以及(3)能够自动检测感兴趣特征的计算机视觉算法。本文还回顾了从图像中重建提取特征的几何表示的现有方法,以及解决数据质量问题的潜在方法。进行了初步实验,证实了免费提供的Mapillary图像可用于检测地下室栏杆作为地下室特征的示例类型,以及对特征进行地理定位。
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引用次数: 0
KI spielt StarCraft 2 auf Profiniveau 理性小理性
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-01-01 DOI: 10.1007/978-3-662-62492-0_12
Daniela Mocker
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引用次数: 0
Mysteriöse Materialien 神秘的材料
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-01-01 DOI: 10.1007/978-3-662-62492-0_18
M. Groß
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引用次数: 0
KI sucht nach neuer Physik KI在寻找新的物理学
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-01-01 DOI: 10.1007/978-3-662-62492-0_19
Philipp Hummel
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引用次数: 0
Lange gesund leben – dank KI 健康长寿——感谢人工智能
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-01-01 DOI: 10.1007/978-3-662-62492-0_25
Eva Wolfangel
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引用次数: 0
Armut auf der Spur 贫困的踪迹
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-01-01 DOI: 10.1007/978-3-662-62492-0_14
Lisa Vincenz-Donnelly
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引用次数: 0
Maschinen mit menschlichen Zügen 驾驶人类列车的机器
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-01-01 DOI: 10.1007/978-3-662-62492-0_5
George Musser
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引用次数: 0
Wo hat sie das nur gelernt? 她从哪儿学来的?
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-01-01 DOI: 10.1007/978-3-662-62492-0_23
Eva Wolfangel
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引用次数: 0
KI lernt die Sprache der Mathematik 人工智能学习数学
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-01-01 DOI: 10.1007/978-3-662-62492-0_6
Manon Bischoff
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引用次数: 0
Some Thoughts on AI Stimulated by Michael Wooldridge's Book "The Road to Conscious Machines. The Story of AI". Michael Wooldridge的书《通往有意识机器之路》激发了人们对人工智能的一些思考。《AI的故事》。
IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-01-01 DOI: 10.1007/s13218-022-00769-3
W F Bodmer

Following a brief over view of the contents of Michael Wooldridge's book I give an account of my own background in computing and AI. I then cover a range of topics stimulated by reading the book including machine learning's relationship to AI, applications to medical areas, the need to consider probabilistic effects on decisions, the importance of self-reproduction and whether AI can be made moral. I finish with a discussion of the mind-brain relationship and what makes us human.

在对迈克尔·伍尔德里奇(Michael Wooldridge)这本书的内容进行简要概述之后,我将介绍自己在计算和人工智能方面的背景。然后,我涵盖了一系列因阅读这本书而激发的主题,包括机器学习与人工智能的关系、在医学领域的应用、考虑决策的概率影响的必要性、自我复制的重要性以及人工智能是否可以成为道德的。最后,我讨论了心智与大脑的关系,以及是什么让我们成为人类。
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引用次数: 24
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