References
[1]. Arivazhagan, S., Shebiah, R. N., Ananthi, S., & Varthini, S. V. (2013). Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features. Agricultural Engineering International: CIGR Journal, 15(1), 211-217.
[2]. Barbedo, J. G. A. (2016). A review on the main challenges in automatic plant disease identification based on visible range images. Biosystems Engineering, 144, 52-60.
[3]. Bock, C. H., & Nutter Jr, F. W. (2012). Detection and measurement of plant disease symptoms using visiblewavelength photography and image analysis. Plant Sciences Reviews, 2011, 73.
[4]. Camargo, A., & Smith, J. S. (2009). Image pattern classification for the identification of disease causing agents in plants. Computers and Electronics in Agriculture, 66(2), 121-125.
[5]. Cen, Z. X., Li, B. J., Shi, Y. X., Huang, H. Y., Liu, J., Liao, N. F. et al. (2007). Discrimination of cucumber anthracnose and cucumber brown speck base on color image statistical characteristics. Acta Horticulturae Sinica, 34(6), 1425.
[6]. Omrani, E., Khoshnevisan, B., Shamshirband, S., Saboohi, H., Anuar, N. B., & Nasir, M. H. N. M. (2014). Potential of radial basis function-based support vector regression for apple disease detection. Measurement, 55, 512-519.
[7]. Phadikar, S., & Sil, J. (2008, December). Rice disease identification using pattern recognition techniques. In Computer and Information Technology, 2008. ICCIT th 2008. 11 International Conference on (pp. 420-423). IEEE.
[8]. Pujari, J. D., Yakkundimath, R., & Byadgi, A. S. (2015). Image processing based detection of fungal diseases in plants. Procedia Computer Science, 46, 1802-1808.
[9]. Rastogi, A., Arora, R., & Sharma, S. (2015, February). Leaf disease detection and grading using computer vision technology and fuzzy logic. In Signal Processing nd and Integrated Networks (SPIN), 2015 2 International Conference on (pp. 500-505). IEEE.
[10]. Revathi, P., & Hemalatha, M. (2012, December). Classification of cotton leaf spot diseases using image processing edge detection techniques. In Emerging Trends in Science, Engineering and Technology (INCOSET), 2012 International Conference on (pp. 169- 173). IEEE.
[11]. Rothe, P. R., & Kshirsagar, R. V. (2015, January). Cotton leaf disease identification using pattern recognition techniques. In Pervasive Computing (ICPC), 2015 International Conference on (pp. 1-6). IEEE.
[12]. Sannakki, S. S., & Rajpurohit, V. S. (2015). Classification of Pomegranate Diseases based on Back Propagation Neural Network. International Research Journal of Engineering and Technology (IRJET), 2(2).
[13]. Tian, Y., Zhao, C., Lu, S., & Guo, X. (2012, June). SVMbased Multiple Classifier System for recognition of wheat leaf diseases. In World Automation Congress (WAC), 2012 (pp. 189-193). IEEE.
[14]. Vipinadas, M. J., Thamizharasi, A., (2015). A Survey on Plant Disease Identification. International Journal of Computer Science Trends and Technology (IJCST), 3(6), 129-135.
[15]. Wang, H., Li, G., Ma, Z., & Li, X. (2012, October). Image recognition of plant diseases based on backpropagation networks. In Image and Signal th Processing (CISP), 2012 5 International Congress on (pp. 894-900). IEEE.
