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              <text>Detection of Disease in Mango Trees Using Color Features of Leaves</text>
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              <text>Color analysis; Disease detection; Feature extraction; Mango trees; Neural network; Region of interest; Segmenting</text>
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              <text>The goal has been to detect disease in mango trees. This paper compares different approaches to extract color features and check the accuracy and applicability for mango trees. The paper proposes variations which helped in increasing the accuracy of features extracted for mango trees: firstly, a customized method of splitting leaf into layers while doing K-means clustering, and secondly, segmenting the region of interest to blocks to help in applying statistical functions more accurately over a region.  2020, Springer Nature Singapore Pte Ltd.</text>
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              <text>Jos J.; Venkatesh K.A.</text>
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              <text>Lecture Notes in Networks and Systems, Vol-103, pp. 583-593.</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-15-2043-3_63" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-15-2043-3_63&lt;/a&gt;
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              <text>ISSN: 23673370</text>
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              <text>Jos J., Christ University, Hosur Road, Bengaluru, India; Venkatesh K.A., Myanmar Institute of Information Technology, Chanmyathazi, Myanmar</text>
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