• POORNIMA
• NANDINI
• NITISH
• SHILPA
• SWATHI

This research work focused on automatic detection method for image analysis on rice leaves under wide range of natural condition for further analysis. In image processing the syndrome is an essential part for feature eradication and regulation. However, some of the threats are still flawed to predict the inflammation. To meet those threats, the expected algorithm focuses on an exact problem to predict the inflammation from early warning. Bacterial Leaf Blight and Brown Spot are a major bacterial and fungal inflammation respectively in rice (Oryza sativa) crops, it causes harvest loss and reduce the grains quality. Various hybrid techniques for image analysis and regulation algorithms were analyzed and an automatic detection method has been proposed for identifying the XACT inflammation in rice leave sunder different natural condition

"RICE LEAF DISEASE DETECTION USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.k343-k346, May-2023, Available :http://www.jetir.org/papers/JETIR2305A47.pdf

"RICE LEAF DISEASE DETECTION USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppk343-k346, May-2023, Available at : http://www.jetir.org/papers/JETIR2305A47.pdf