There is an upcoming webinar dedicated to Machine learning algorithms and their use for detection of objects in satellite images. The webinar is scheduled for Wednesday 1st April 2020 and below you can find the overview and more details.
DURING THIS FREE WEBINAR YOU WILL LEARN:
- Why is field boundaries detection important for agriculture?
- What are current emphasis on AI in relation to satellite data?
- What ML algorithms can be used for land cover classification?
- Learn more about Using ML for detection of Land Use Objects
- Introduction to datacubes, OGC coverages, coverage services, rasdaman, python API,
- Services available for both Dubrovnik INSPIRE hackathon and Kampala INSPIRE hackathon challenges.
What: In this webinar we will explore possible machine learning algorithms and artificial neural networks that can be used for field boundaries detection from Sentinel 2 or Landsat images. Relevance to several of the Dubrovnik INSPIRE hackathon challenges as well as challenges of the Kampala INSPIRE hackathon will be highlighted.
Why: Accurate information on field boundaries is very important input for many reasons: eg. having accurate information on crop types and boundary defining a given soil block, we can for example determine the yield potential or the amount of fertilizer needed for given type of crop very precisely.
One of the possible ways is to exploit the potential of satellite imagery (Sentinel 2 or Landsat images), which provide a wealth of information about Earth’s surface and are available as open data. In conjunction with machine learning algorithms, we can get very interesting inputs for precision agriculture.
Who (is the webinar for): Academia & Research Researchers and Innovators who are engaged with solution of challenges related to AI and satellite images. Farmers’ associations and agricultural companies. Any possible participant of the Kampala Hackathon, who is considering his/her participation in this challenge.
If you are interested in this topic, do not hesitate to register HERE!