• Vanaja Karupally

This paper aims to provide a overview of machine learning (ML) techniques across various data types, fostering opportunities to address research gaps and advance the field, particularly in the detection and prediction of crop diseases. The survey presents valuable insights into SVM and Random Forest Models for detection and prediction of Crop dieseases.

Machine learning, SVM, Random forest, plant disease detection

"SVM and Random Forest Models for Detection and Prediction of Crop Diseases ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 12, page no.h763-h767, December-2023, Available :http://www.jetir.org/papers/JETIR2312792.pdf

"SVM and Random Forest Models for Detection and Prediction of Crop Diseases ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 12, page no. pph763-h767, December-2023, Available at : http://www.jetir.org/papers/JETIR2312792.pdf