IEEE

Deep Learning Models for Precision Agriculture: Evaluating CNN Architectures for Accurate Plant Disease Detection

Abstract: Early and precise detection of plant diseases is crucial for enhancing crop yield and minimizing agricultural losses. This paper evaluates the performance of deep learning-based ...
IEEE

Capsicum Plant Advanced Disease Detection Using CNN-SVM Fusion for Precision Crop Protection

Abstract: With the use of a combination of cutting-edge deep learning techniques, such as artificial neural networks, convolutional neural networks, and support vector machines, a unique method for ...
IEEE

Early Cotton Plant Disease Detection using Drone Monitoring and Deep Learning

Abstract: India is the largest contributor of cotton production in the world but at recent times the cotton production has been decreased significantly due to various cotton plant diseases. The ...
Frontiers

Advanced hyperspectral image processing and machine learning approaches for early detection of wheat stem rust

1 Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia 2 All-Russian Institute of Plant Protection, Saint Petersburg, Russia However, despite rapid methodological advances, ...
IEEE

Roses Plant Disease Detection using DenseNet121 Model

Abstract: Roses diseases pose a significant threat to horticultural productivity, necessitating early detection and intervention for effective management. This research proposes the development of a ...
Frontiers

Multiscale CNN-state space model with feature fusion for crop disease detection from UAV imagery

Accurate detection of crop diseases from unmanned aerial vehicle (UAV) imagery is critical for precision agriculture. This task remains challenging due to the complex backgrounds, variable scales of ...