DETECTION OF DISEASES FROM CROP LEAF IMAGES USING MACHINE LEARNING TECHNIQUES: A REVIEW

DETECTION OF DISEASES FROM CROP LEAF IMAGES USING MACHINE LEARNING TECHNIQUES: A REVIEW

Bhavana Bhaskar Hegde¹,  C Chithra Lekha², Harshleen Kaur³  , Pavitra Ramachandra Gouda⁴  , Mrs. K.P Mayuri⁵

¹UG Student, Dept. of CSE, Sir M. Visvesvaraya Institute Of Technology

²UG Student, Dept. of CSE, Sir M. Visvesvaraya Institute Of Technology

³UG Student, Dept. of CSE, Sir M. Visvesvaraya Institute Of Technology

⁴UG Student, Dept. of CSE, Sir M. Visvesvaraya Institute Of Technology

⁵  Assistant Professor , Dept. of CSE, Sir M. Visvesvaraya Institute Of Technology

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Abstract - Agriculture plays a vital role in our day-to-day life. Identification of the disease of plant leaves is very important to prevent the losses in the yield. The plant diseases such as fungi, bacteria and viruses. The leaf diseases completely destroy the quality of the leaf. In this review we present some critical survey on the challenges which we are currently facing and also various methodology which includes Machine learning, deep learning and image processing algorithms which are tested on various plant leaves to detect diseases which helps to increase the yield.

Finally, we identify the challenges and some opportunities for future developments in this area

Key Words: Image processing; Machine Learning; classification; SVM, CNN, Deep Learning, Disease, Neural network