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土耳其种植的认证水稻  Osmancik品种和Cammeo品种数据集

土耳其种植的认证水稻 Osmancik品种和Cammeo品种数据集

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Computer Classification

Ilkay CINARGraduate School of Natural and Applied Sciences, Selcuk University, TURKEY,ORCID ID : 0000-0003-0611-3316lkay......

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    README.md

    Ilkay CINAR
    Graduate School of Natural and Applied Sciences,
    Selcuk University,
    TURKEY,
    ORCID ID :  0000-0003-0611-3316
    lkay_cinar '@' hotmail.com

    Murat KOKLU
    Faculty of Technology,
    Selcuk University,
    TURKEY.
    ORCID ID :  0000-0002-2737-2360
    mkoklu '@' selcuk.edu.tr


    Data Set Information:

    Among  the certified rice grown in TURKEY,  the  Osmancik species, which has a large planting area since 1997 and the Cammeo species grown since 2014 have been selected for the study.  When  looking  at  the  general  characteristics  of  Osmancik species, they have a wide, long, glassy and dull appearance.  When looking at the general characteristics of the Cammeo species, they have wide and long, glassy and dull in appearance.  A total of 3810 rice grain's images were taken for the two species, processed and feature inferences were made. 7 morphological features were obtained for each grain of rice.


    Attribute Information:

    1.) Area: Returns  the  number  of  pixels  within  the boundaries of the rice grain.
    2.) Perimeter: Calculates the circumference by calculating  the  distance  between  pixels around the boundaries of the rice grain.
    3.) Major Axis Length: The longest line that can be drawn on the rice  grain,  i.e.  the  main  axis  distance, gives.
    4.) Minor Axis Length: The shortest line that can be drawn on the rice  grain,  i.e.  the  small  axis  distance, gives.
    5.) Eccentricity: It measures how round the ellipse, which has  the  same  moments  as  the  rice  grain, is.
    6.) Convex Area: Returns  the  pixel  count  of  the  smallest convex shell of the region formed by the rice grain.
    7.) Extent: Returns the ratio of the regionformed by the rice grain to the bounding box pixels.
    8.) Class: Cammeo and Osmancik rices


    Relevant Papers:

    Cinar, I. and Koklu, M. (2019). Classification of Rice Varieties Using Artificial Intelligence Methods. International Journal of Intelligent Systems and Applications in Engineering,  vol.7, no.3 (Sep. 2019), pp.188-194. ([Web link])



    Citation Request:

    Cinar, I. and Koklu, M. (2019). Classification of Rice Varieties Using Artificial Intelligence Methods. International Journal of Intelligent Systems and Applications in Engineering,  vol.7, no.3 (Sep. 2019), pp.188-194. ([Web link])

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