Sep
18

GeoMonday 2017.3 - Geo AI (powered by Esri)

Created by a.erbeesri-de-esridist Employee on Aug 9, 2017

Monday, September 18, 2017 at OfficeClub (ex MobileSuite)

Starts at 10:00 AM · Ends at 1:00 PM, PST (America/Los_Angeles)

  • a.erbeesri-de-esridist

Geo Geeks listen up!

 

Nowadays „Artificial Intelligence“ celebrates its comeback to the top-IT-buzzword-lists. Neverthless, the topic is around for decades. But in the recent years, significant progresses have been made. We see a wide range of new business models and applications also in the geo area, which are made possible by ever-improving pattern recognition algorithms and machine learning technologies. Transforming geodata into loaction meaning also powers next generation decision-making systems that are now being available for all kind of users. More and more systems are becoming at least semi-autonomous and proposing smart suggestions, which will change the way we interact with and perceive geo-spatial applications.

 

Esri is happily supporting GeoMonday and we would love to see you all there. Get your tickets for the 3th GeoMonday 2017 now at: http://geomonday2017-3.eventbrite.de

 

Speakers:

 

Michael Marz, Esri Deutschland:

How neural networks make GIS-supported crop production more efficient

High-tech has already arrived in agriculture. Modern agricultural machinery and geographic information systems make precision farming possible. An important aspect in crop production is the basic fertilization with nutrients and additives. The pH value can already be determined in a small scale and during the crossing of a tractor with specific sensors. For essential macronutrients like phosphorus, on-site soil sampling as well as complex and cost-intensive determination of the content in the laboratory are still necessary. Phosphorus content depends on chemical and physical soil conditions. If these conditions are known, the content of phosphorus can be estimated. This paper provides extracts from a research project on how neural networks help to estimate local phosphorous content for fertilization by learning those nonlinear multilateral relationships in the soil.

 

mmarz

 

 

Michael Marz is a sales engineer at Esri Deutschland GmbH. Previously, he was a scientific staff member at the University of Halle and conducted research in the thematic field of efficient crop production with focus on fertilization and self-learning algorithms.

 

 

Sebastian Gerke, TerraLoupe:

From aerial images to maps with Deep Learning

With the increasing amount of aerial imagery - regardless if captured from aircrafts or UAV  - available, automatic analysis of this data becomes more and more important to make use of this data. TerraLoupe uses deep neural networks to automatically detect objects of interest for various industries such as automotive, insurance or energy to help their clients getting deeper insights for their business critical applications. This includes high-definition maps for autonomous driving, risk assessment for insurances and solar potential analysis.

 

 

 

 

Sebastian Gerke studied Computer Science at the University of Karlsruhe, after which he worked as a research associate at the Fraunhofer HHI and pursued research in computer vision and machine learning. In 2015 he co-founded TerraLoupe, a startup that brings deep learning expertise to the field of aerial imagery. 

 


Martin Wilden and Matthias Stein, con terra:

Natural language understanding in web mapping applications

"Will speech soon do away with typing?" - This question has recently been raised by a large German newspaper. Lately, more and more speech assistants like Google Assistant, Amazon's Alexa, Mircosoft's Cortana or Apple's Siri are reaching the market and allowing users to control many parts of their life by voice input. This technology is called natural language understanding (NLU) and may also be used to control Web mapping technology. Imagine that you could say "show me all schools in Berlin" instead of using a selection tool to select those features.

 

 

 

Martin Wilden studied Geoinformatics at the University of Münster. While studying, he worked as student assistant for 52° North Initiative for Geospatial Open Source Software GmbH. After finishing his studies he joined con terra GmbH as software developer.

 

 

 

Matthias Stein is a software engineer at con terra GmbH. Previously he studied Geoinformatics at the Hochschule Bochum University of Applied Science.  

 

 

If you want to present your related products and/or service story, please contact info@geomonday.org and provide your headline and some background information.

 

BTW, catering is for free

 

Your GeoDev Germany Team

 

 

GeoMonday

OfficeClub (ex MobileSuite)

Pappelallee 78/79 10437 Berlin Germany