ºÝºÝߣshows by User: jyoong / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: jyoong / Mon, 20 Nov 2017 20:16:40 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: jyoong The Future of Maps for Mobility / Geography2050 /slideshow/the-future-of-maps-for-mobility-geography2050-82404383/82404383 geography2050-ignitetalk-janineyoong-171120201640
While high-resolution satellite imagery is the foundation of digital mapping, the demands of urban mobility require highly accurate, frequently updated data from a different vantage point – the ground. Recent advances in street-level imagery collection and data extraction are lifting up new trends in location-based services, smart cities, and autonomous vehicles. As map technologists push the boundaries of machine intelligence for extracting data from images, human collaboration will drive the creation of maps for mobility for all.]]>
While high-resolution satellite imagery is the foundation of digital mapping, the demands of urban mobility require highly accurate, frequently updated data from a different vantage point – the ground. Recent advances in street-level imagery collection and data extraction are lifting up new trends in location-based services, smart cities, and autonomous vehicles. As map technologists push the boundaries of machine intelligence for extracting data from images, human collaboration will drive the creation of maps for mobility for all.]]> Mon, 20 Nov 2017 20:16:40 GMT /slideshow/the-future-of-maps-for-mobility-geography2050-82404383/82404383 jyoong@slideshare.net(jyoong) The Future of Maps for Mobility / Geography2050 jyoong While high-resolution satellite imagery is the foundation of digital mapping, the demands of urban mobility require highly accurate, frequently updated data from a different vantage point – the ground. Recent advances in street-level imagery collection and data extraction are lifting up new trends in location-based services, smart cities, and autonomous vehicles. As map technologists push the boundaries of machine intelligence for extracting data from images, human collaboration will drive the creation of maps for mobility for all. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/geography2050-ignitetalk-janineyoong-171120201640-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> While high-resolution satellite imagery is the foundation of digital mapping, the demands of urban mobility require highly accurate, frequently updated data from a different vantage point – the ground. Recent advances in street-level imagery collection and data extraction are lifting up new trends in location-based services, smart cities, and autonomous vehicles. As map technologists push the boundaries of machine intelligence for extracting data from images, human collaboration will drive the creation of maps for mobility for all.
The Future of Maps for Mobility / Geography2050 from Janine Yoong
]]> 611 4 https://cdn.slidesharecdn.com/ss_thumbnails/geography2050-ignitetalk-janineyoong-171120201640-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-jyoong-48x48.jpg?cb=1529069334 Street-level imagery for map data at scale www.mapillary.com