The project utilizes the capabilities of deep learning to create an efficient and dependable system for automated crop disease detection. Deep learning can extract patterns and features from …

This paper proposes a smart and efficient technique for detection of crop disease which uses computer vision and machine learning techniques. The proposed system is able to detect 5 …

The integration of Machine Learning (ML) and Deep Learning (DL) in agriculture has surged, addressing farming challenges through crop recommendation, fertilizer optimization, and plant …

This project is created with the goal of detecting the disease of crop through its leaf. In this project concept of deep learning is used which uses the concept of neural networks to solve the …

Sep 30, 2019 · The proposed approaches involves pre-processing of input image and the paddy plant disease type is recognized using Gray-Level Co-occurrence Matrix (GLCM) technique …

learning algorithms and image processing techniques to construct an automated system for the detection of plant diseases. A large dataset with labeled photos of both healthy and infected …

In this study, a pre-trained convolutional neural network (CNN) was employed to create an android-based recognition tool for recognizing corn diseases. A dataset of healthy corn leaves …

May 5, 2023 · To develop this system, construction of a stepwise disease detection model using images of diseased-healthy plant pairs and a CNN algorithm consisting of five pre-trained …

Aug 18, 2018 · This paper proposes a deep learning-based model which is trained using public dataset containing images of healthy and diseased crop leaves. The model serves its objective …

To address this challenge, a deep learning-based system has been developed to identify crop diseases and provide recommendations for suitable plants. The system utilizes RGB images …