Leveraging the ResNet- 9 architecture, the plant disease classification model accurately identifies diseases in crop leaves. Additionally, the system incorporates crop prediction capabilities to …

Sep 27, 2024 · We systematically examine various crops and diseases, employing a range of ML/AI strategies for detection. Tailored crop disease detection models for specific regions and …

Aug 16, 2023 · In , using machine learning, the authors proposed a system for the early prediction of crop diseases in plants by utilizing the Convolutional Neural Network (CNN) method. The …

The project focuses on building a mobile and web-based application that uses machine learning algorithms to identify crop diseases and offer treatment recommendations based on real-time …

Dec 1, 2023 · Proposed a deep learning-based model for crop disease detection. Provides a higher accuracy rate of 98.98% using ResNet-50 for disease detection. Ensure farmers save …

The AI-driven crop disease prediction system provides an efficient and accurate solution for identifying crop diseases using two distinct approaches: image-based prediction and …

To analyze the data that has been gathered and identify the presence of illnesses in crops based on image analysis and environmental factors, machine learning algorithms are utilized.

that combines machine learning (ML) algorithms with Internet of Things (IoT) devices for all-encompassing agriculture management. The technology provides a unified method for disease …

Accurate crop prediction is essential to maximize yield and optimize resource usage, ensuring food security and economic stability. This paper presents an advanced model that integrates …

Feb 3, 2025 · Machine Learning algorithms enable precise crop disease detection. These algorithms learn from historical data and adapt over time. As a result, they become more …