Abstract
Tracking the spread of viral crop diseases is critically important in developing countries. It is also a problem in which several data analysis techniques can be applied in order to get more reliable information more quickly and at lower cost. This paper describes some novel ways in which computer vision, spatial modelling, active learning and optimisation can be applied in this setting, based on experiences of surveying viral diseases affecting cassava and banana crops in Uganda.
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Quinn, J. (2013). Computational Techniques for Crop Disease Monitoring in the Developing World. In: Tucker, A., Höppner, F., Siebes, A., Swift, S. (eds) Advances in Intelligent Data Analysis XII. IDA 2013. Lecture Notes in Computer Science, vol 8207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41398-8_2
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DOI: https://doi.org/10.1007/978-3-642-41398-8_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41397-1
Online ISBN: 978-3-642-41398-8
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