Assessing Damage - Revision history

BPeat: Text replacement - "http:" to "https:"

2023-03-28T05:19:28Z

Text replacement - "http:" to "https:"

BPeat at 13:04, 16 January 2023

2023-01-16T13:04:24Z

BPeat at 12:20, 23 September 2020

2020-09-23T12:20:18Z

BPeat at 17:01, 11 September 2020

2020-09-11T17:01:57Z

BPeat: /* Earthquake */

2020-09-11T16:59:20Z

‎Earthquake

BPeat at 16:51, 11 September 2020

2020-09-11T16:51:01Z

BPeat at 16:42, 11 September 2020

2020-09-11T16:42:17Z

BPeat at 16:31, 11 September 2020

2020-09-11T16:31:31Z

BPeat: /* Earthquake */

2020-09-11T16:30:28Z

‎Earthquake

BPeat: /* Earthquake */

2020-09-11T16:25:04Z

‎Earthquake

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 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
-[http://www.youtube.com/results?search_query=Climate+Change+Planetary+Health+Risks+artificial+intelligence+deep+machine+learning Youtube search...]
+[https://www.youtube.com/results?search_query=Climate+Change+Planetary+Health+Risks+artificial+intelligence+deep+machine+learning Youtube search...]
-[http://www.google.com/search?q=Climate+Change+Planetary+Health+Risks+artificial+intelligence+deep+machine+learning ...Google search]
+[https://www.google.com/search?q=Climate+Change+Planetary+Health+Risks+artificial+intelligence+deep+machine+learning ...Google search]
 * [[Case Studies]]
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 <youtube>m24GfyFzSX0</youtube>
 <b>Assessing Property Damage with AI
-</b><br>The critical task of damage claim processing is typically labor-intensive and requires a significant amount of time.  The deep learning tools within Esri ArcGIS sped up the process to provide aid to those affected by the Woolsey fire. This demo shows the workflow used; from training the deep learning model to inferring which automated the detection of damaged homes. For this demo, we used a client-server architecture which gives a clean separation of the roles of a Geographic Information System (GIS) Analyst and a Data Scientist. The GIS Analyst uses NVIDIA Quadro Virtual Data Center Workstation (Quadro vDWS) software to create, edit and explore spatial data. The Data Scientist uses [[NVIDIA]] Virtual Compute Server (vComputeServer) software to train/build a model which will then be used by the GIS Analyst to execute object detection inferencing. "To learn more about virtualization in the data center, and to try building and running this demo yourself using free trails of both virtual GPUs and ArcGIS (including the  imagery used in this study from [http://www.nvidia.com/en-us/data-center/virtualization/resources/ OpenAerialMap])
+</b><br>The critical task of damage claim processing is typically labor-intensive and requires a significant amount of time.  The deep learning tools within Esri ArcGIS sped up the process to provide aid to those affected by the Woolsey fire. This demo shows the workflow used; from training the deep learning model to inferring which automated the detection of damaged homes. For this demo, we used a client-server architecture which gives a clean separation of the roles of a Geographic Information System (GIS) Analyst and a Data Scientist. The GIS Analyst uses NVIDIA Quadro Virtual Data Center Workstation (Quadro vDWS) software to create, edit and explore spatial data. The Data Scientist uses [[NVIDIA]] Virtual Compute Server (vComputeServer) software to train/build a model which will then be used by the GIS Analyst to execute object detection inferencing. "To learn more about virtualization in the data center, and to try building and running this demo yourself using free trails of both virtual GPUs and ArcGIS (including the  imagery used in this study from [https://www.nvidia.com/en-us/data-center/virtualization/resources/ OpenAerialMap])
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 <youtube>VWpRM7-xfyc</youtube>
 <b>TechLearnTalk - An Introduction to AI - WFP Case Study
-</b><br>SKAI Artificial intelligence and aerial imagery in emergencies; uses Artificial Intelligence (AI) and satellites to help World Food Program (WFP) reduce the amount of time needed to understand the impact of disasters.  By using Artificial Intelligence (AI) to analyze images provided by satellites, WFP can respond to emergencies without the delays and logistics obstacles associated with a traditional response. Skai dramatically speeds up the process of determining what has happened, what to expect on the ground, and help define the kind of support that is required.  UN Innovation Network. Your gift could be the difference between a child going to bed hungry or eating a nutritious meal. WFP does whatever it takes to deliver lifesaving food to children and families most in need, wherever they are in the world, by providing meals in schools, distributing staples during emergencies and delivering food vouchers in conflict zones.  http://secure.wfpusa.org/donate/save-lives-giving-food-today-donate-now-29
+</b><br>SKAI Artificial intelligence and aerial imagery in emergencies; uses Artificial Intelligence (AI) and satellites to help World Food Program (WFP) reduce the amount of time needed to understand the impact of disasters.  By using Artificial Intelligence (AI) to analyze images provided by satellites, WFP can respond to emergencies without the delays and logistics obstacles associated with a traditional response. Skai dramatically speeds up the process of determining what has happened, what to expect on the ground, and help define the kind of support that is required.  UN Innovation Network. Your gift could be the difference between a child going to bed hungry or eating a nutritious meal. WFP does whatever it takes to deliver lifesaving food to children and families most in need, wherever they are in the world, by providing meals in schools, distributing staples during emergencies and delivering food vouchers in conflict zones.  https://secure.wfpusa.org/donate/save-lives-giving-food-today-donate-now-29
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 <youtube>ts3yxfNrDnY</youtube>
 <b>FireNET - Real-time fire detection with AI
-</b><br>FireNet is a real-time fire detection project created to ensure that artificial intelligence systems can be trained to detect fires instantly and eliminate false alerts. Learn more via the GitHub link below. http://github.com/OlafenwaMoses/FireNET
+</b><br>FireNet is a real-time fire detection project created to ensure that artificial intelligence systems can be trained to detect fires instantly and eliminate false alerts. Learn more via the GitHub link below. https://github.com/OlafenwaMoses/FireNET
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 <b>Motor Insurance Accident Assist | GL Projects Showcase AI & ML | Great Learning
 </b><br>Our Vision to provide human comparable intelligent services to the insurance industry at a low cost. Our Mission is empowering insurers to provide quick, efficient and transparent customer engagement through technology. In short-term we would Eliminate the need for physical inspection required on minor accidents by 100%, Reduce the processing time to complete accident based claims by 90%*, Bring transparency and consistency in claim procedures, And for long term 2-3 Years - Eliminate manual inspections for major accidents*, 4-5 Years - Expand to Europe and the Americas.
-Visit Great Learning Academy, to get access to 80+ free courses with 1000+ hours of content on Data Science, Data Analytics, Artificial Intelligence, Big Data, Cloud, Management, Cybersecurity and many more. These are supplemented with free projects, assignments, datasets, quizzes. You can earn a certificate of completion at the end of the course for free. http://glacad.me/3duVMLE
+Visit Great Learning Academy, to get access to 80+ free courses with 1000+ hours of content on Data Science, Data Analytics, Artificial Intelligence, Big Data, Cloud, Management, Cybersecurity and many more. These are supplemented with free projects, assignments, datasets, quizzes. You can earn a certificate of completion at the end of the course for free. https://glacad.me/3duVMLE
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 <youtube>4brsOwZzHbo</youtube>
 <b>Unleash live - Fire Damage A.I.
-</b><br>Powerful live video streaming for detecting and assessing structural damage due to fire.
+</b><br>Powerful live [[Video|video]] streaming for detecting and assessing structural damage due to fire.
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 ** [[Transportation (Autonomous Vehicles)]]
 ** [[Risk, Compliance and Regulation]]
-* [[Explainable Artificial Intelligence (XAI)]]
+* [[Explainable / Interpretable AI]]
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 * [[Case Studies]]
 ** [[Meteorology]]
 ** [[Life Sciences]]

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 = <span id="Earthquake"></span>Earthquake =
-* [[Earthquake Prediction]]
+* [[Seismology]]
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-<youtube>ID2</youtube>
+<youtube>7PHVe1-UEs8</youtube>
-<b>HH2
+<b>Damage assessment using deep learning in ArcGIS
-</b><br>BB2
+</b><br>Discover how to leverage deep learning capabilities in the aftermath of a natural disaster to speed up response and recovery efforts.
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 = <span id="Fire"></span>Fire =

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 = <span id="Earthquake"></span>Earthquake =
 * [[Earthquake Prediction]]
 {|<!-- T -->
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 <b>From earthquake to recovery: Assessing damage fast with AI and IoT
 </b><br>A major construction company in Japan is outfitting buildings with artificial intelligence (AI), Internet of Things (IoT), and cloud technologies to automatically detect structural damage fast after a quake – saving lives, time, and money
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