An Innovative Method for Detecting Disease in Maize Crop Leaves using Deep Convolutional Neural Networks

Even though numerous crops have been planted, their production is declining daily due to various crop diseases. The early diagnosis of agricultural diseases is essential for boosting productivity and the financial development of farmers. Crop disease detection is a critical component of contemporary agriculture because it enables farmers to quickly and effectively identify and treat plant illnesses. Early crop disease diagnosis can drastically reduce losses in output and the necessity for excessive pesticide use, making agriculture more profitable and sustainable. The proposed artificial intelligence-based image processing technique is employed to predict early diseases in Maize. A perfect % prediction accuracy of 98.9% was attained when the proposed work was evaluated using images from the agricultural village dataset. The outcomes demonstrated the uniqueness of the research by being comparatively superior to models for transfer learning and pretraining.