Using eCognition to improve feature recognition.

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Presentation of MSc research at the CAA 2016 - Oslo. Session 20 "Computer vision vs human perception in remote sensing image analysis: Time to move on".

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Using eCognition to improve feature recognition.

  1. 1. Using eCognition to improve feature recognition.
  2. 2. Cognitive computing in Geomorphology.
  3. 3. Computing to imitate archaeologists.
  4. 4. Case study: barrow detection using eCognition.
  5. 5. Discussion and future scope.
  6. 6. Roundbarrow Mound Round has shape is defined by … (varied sizes) has size Ditch possibly surrounded by Bank possibly surrounded by Flora Agriculture possibly (partly) levelled Fauna possibly (partly) destroyed has landcover Barrow Earthworkis type of is type of is type of
  7. 7. Thank you.
  8. 8. Barceló, J. A. 2008. Computational Intelligence in Archaeology, Hershey, New York, IGI. Blaschke, T., and Strobl, J. 2001. What's wrong with pixels? Some recent developments interfacing remote sensing and GIS. Geo-Informations-Systeme, 14, 12-17. van den Eeckhaut, M., Kerle, N., Poesen, J., and Herv‡s, J. 2012. Identification of vegetated landslides using only a Lidar-based terrain model and derivatives in an object-oriented environment. Proceedings of the 4th GEOBIA, 211. Niemeyer, I., Marpu, P. R., and Nussbaum, S. 2008. Change detection using object features. In: Blaschke, T., Lang, S., and Hay, G. J. (eds.) Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications. Verlag: Springer. TRIMBLE eCognition Developer 9.1

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