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  1. Land Lines is an experiment that lets you explore Google Earth satellite imagery through gesture. “Draw” to find satellite images that match your every line; “Drag” to create an infinite line of connected rivers, highways and coastlines.

  2. chromewebstore.google.com › detail › land-linesLand Lines - Google Chrome

    Land Lines is an experiment that lets you explore Google Earth satellite imagery through gesture. “Draw” to find satellite images that match your every line; “Drag” to create an infinite line...

  3. Chrome Experiments. Land Lines lets you explore Google Earth satellite images through gesture. Machine learning and line detection algorithms were used to preprocess all images and identify the dominant lines. This enabled the analysis of brushstrokes and retrieval of the matching image efficiently without the need for a server.The project was ...

  4. 27 de dez. de 2016 · Land Lines, um novo experimento do Google Chrome que explora os dados de imagens de satélite coletados pelo Google Maps permite que qualquer pessoa crie contornos cartográficos com simples gestos.

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  5. web.dev › case-studies › land-linesLand Lines | web.dev

    15 de dez. de 2016 · Land Lines is an experiment that lets you explore Google Earth satellite images through gesture. Using a combination of machine learning, optimized algorithms,and graphics card power, the experiment is able to run efficiently on your phone's web browser without a need for backend servers.

  6. "Land Lines" is a Chrome Experiment that leverages the wealth of visual data from satellite images in creative ways. Users can explore Google Earth's satellite imagery through gestures - "Draw" to find images that match your lines; "Drag" to create an infinite line of connected rivers, highways, and coastlines.

  7. 15 de dez. de 2016 · Built in collaboration with Zach Lieberman, Land Lines is an experiment in big visual data that explores themes of connection. We tried several machine learning libraries in our development process. The learnings from that experience can be found in the case study , while the project code is available open-source on Git Hub.