Krishi-Konect: Enhancing Agriculture with Crop Care Solutions

Agricultural disease detection using convolutional neural networks enhances crop yield by providing early and accurate identification of diseases, mitigating crop losses and boosting productivity. While traditional machine learning techniques are still relevant, deep learning, particularly convolutional neural networks, demonstrates superior performance in image-based disease detection and classification tasks, contingent upon adequate data and computational resources.The objective of this research is to investigate and evaluate the effectiveness of deep learning techniques, particularly convolutional neural networks (CNNs), in the detection and classification of plant diseases using image-based analysis.