• B Uma Maheswari
• Venkatesh.Savithri
• K.Nishitha

A new strategy that leverages Convolution Neural Networks (CNNs) has been developed to accurately classify diseases across various types of leaves. This technique provides agriculturalists with an effective instrument for the early detection and accurate treatment of plant diseases by swiftly and accurately recognizing diseases from leaf images. By employing deep learning methods, this system aids in minimizing economic losses and enhancing agricultural output. Moreover, it showcases the possibility of utilizing deep learning for the detection of plant diseases in different crops, promoting environmentally friendly farming practices.

Classification, class imbalance, Leaf disease, CNN, Mobile net

"A NOVEL METHOD IN THE FIELD OF DEEP LEARNING FOR THE IDENTIFICATION OF LEAF DISEASES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.i385-i392, June-2024, Available :http://www.jetir.org/papers/JETIR2406840.pdf

"A NOVEL METHOD IN THE FIELD OF DEEP LEARNING FOR THE IDENTIFICATION OF LEAF DISEASES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. ppi385-i392, June-2024, Available at : http://www.jetir.org/papers/JETIR2406840.pdf