[Igeba] Rv: [Register today] Geo Hackathon at AGU, Dec 10 2017

Maria Elena Rodriguez Areal mrodriguezareal en yahoo.com.ar
Mar Dic 5 20:54:15 ART 2017 


Enviado desde Yahoo Mail para Android 
 
   ----- Mensaje reenviado ----- De: "ZEISS Geosciences Team" <communications en microscopy.zeiss.com> Para: "mrodriguezareal en yahoo.com.ar" <mrodriguezareal en yahoo.com.ar> Cc:  Enviado: mar., 5 de dic. de 2017 a la(s) 20:52 Asunto: [Register today] Geo Hackathon at AGU, Dec 10 2017   
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|  ZEISS Microscopy
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|   Test your skills against other Geo professionals and win bragging rights and some pretty cool ZEISS optical equipment

 Register now
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|  Geo Hacks 
Sunday, December 10, 2017 at AGU 
New Orleans Downtown Marriott at the Convention Center
Noon – 5:00 p.m. CST (but we'll keep feeding you if you're still going!)
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Dear Maria Elena,

One of the most challenging aspects of microstructural analysis is image processing and segmentation. Frequently image classification and analysis is only possible for a trained human and is impossible to get a machine to perform. Machine learning has transformed many areas of our lives, including the way we shop, the way we search – even the way we date! 

This hackathon – hosted by ZEISS Microscopy at AGU 2017 – aims to bring microstructural analysis into the digital age, and see how we can use these tools to give insights into our data that were previously inaccessible or tedious and painstaking to extract. 

Each team will choose a challenge with the winners receiving a prize of ZEISS field binoculars or handheld magnifiers, courtesy of ZEISS Microscopy. Challenges include:
     
   - Mineralogical segmentation of optical petrography datasets   

   - Correlative mineral identification using both light and electron microscopy dataset    

   - 3D mineral identification using correlated electron and X-ray microscopy datasets    

   - 3D lithological classification of heterogeneous samples   

  
All levels of coding are welcome, and assistance will be provided for those who want to learn. Data for the challenges, computational facilities, and (of course) food and drink will be provided for all attendees all day!
    
| Register now |

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 Lithological classification of two rock types using machine learning. Top: a 1†aolean heterogeneous sandstone core, with high poroperm layers shown in green, low poroperm layers shown in red and a fracture shown in blue. Bottom: A 4†whole core classified using machine learning into high porosity (red) and low porosity (blue) lithologies.  |

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|   Contact us if you'd like to learn more about this event or how ZEISS Microscopy can help solve your geoscience challenges. 

The Geosciences Team ZEISS Microscopy   |
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