Weather and a part of day recognition in the photos using a KNN methodology
Tomasz Krzywicki
Abstrakt
This article presents a proposal for recognizing the weather and part of a day in digital photos encoded in the bitmap format, based on auctorial edge detection algorithm of horizon to demarcate the sky and k-nearest neighbours algorithm, to classify the daytime in the picture as “day” or “night” and to classify the weather as “sunny” or “cloudy”. To verify the effectiveness of the classification the Internal Bagging-5 model was applied. The data for surveys in the form of pictures was prepared on self-provision. To test the method in a different location, data from the Internet was used.
Słowa kluczowe:
image analysis, machine learning, classificationBibliografia
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ARTIEMJEW P., Wybrane paradygmaty sztucznej inteligencji, PJATK Publishing House, 2016
MACHOVÁ K., BARČÁK F., BEDNÁR P.: A Bagging Method using Decision Trees in the Role of Base Classifiers, http://people.tuke.sk/kristina.machova/pdf/bagging_o6.pdf
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MOLINARO, A.M., SIMON, R., PFEIFFER, R.M.: Prediction error estimation. a comparison of resampling methods, in. Bioinformatics, vol. 21, issue 15, Oxford University Press, Oxford, UK, pp. 3301-3307, 2005
Krzywicki, T. (2018). Weather and a part of day recognition in the photos using a KNN methodology. Technical Sciences, 21(4), 291–302. https://doi.org/10.31648/ts.4174
Tomasz Krzywicki
