Sep 1, 2022 · This paper presents a literature review on ML techniques used in the agricultural sector, focusing on the tasks of classification, detection, and prediction of diseases and pests, …

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 …

Dec 1, 2024 · By leveraging appropriate feature selection and extraction methods, researchers can optimize the performance of machine learning models in crop disease detection, enabling …

The dataflow diagram demonstrates the integration of different components, including machine learning models, data processing modules, and external services, to create a cohesive and …

In this paper, a real-time system to identify the type of disease present in a crop based on leaf images using machine learning is proposed. A deep convolutional neural network architecture...

Machine learning-based crop disease detection and classification techniques have gained significant attention in agriculture for early and accurate diagnosis of plant diseases.

Crop disease detection using deep learning incorporates multi-spectral imaging and convolutional neural networks (CNNs). This innovative approach integrates data from diverse spectral bands …

This paper aims at achieving two functionalities which are detection of various parts of a crop and what disease it carries if there is any. The Images are tested with various machine learning …

machine learning approaches for effective crop disease identification and monitoring. The suggested system gathers. data from agricultural areas by using a variety of sensors and …

In recent years, machine learning (ML) has emerged as a powerful tool for automating crop disease detection, enabling timely and accurate identification of plant health conditions. This …