IEEE

Cotton Plant Disease Detection: A Deep Learning Approach

Abstract: Cotton plays a crucial role in the global economy and is a primary raw material for the textile sector. Despite its importance, cotton crops are prone to various diseases that can severely ...

Florida looks to detect crop disease early with drones, AI as nation’s 3rd celery producer

As the nation’s third-leading producer of celery, Florida’s celery fields are valuable crops in the winter but susceptible to ...
IEEE

Hybrid CNN-Swin Framework for Detection and Classification of Potato Leaf Diseases

Abstract: Timely and accurate identification of plant diseases is essential for sustainable agricultural practices and food security. This study presents a deep learning-based diagnostic framework ...
IEEE

CNN-Powered Mobile Based Ayurvedic Plant Identification and Leaf Disease Detection

Abstract: Medicinal plants are another good source for different types of natural compounds and ayurveda as an Indian traditional medicine also uses a lot of medicinal plants with their nutritive, ...
IEEE

Plant Disease Detection Based on Machine Learning Algorithms

Abstract: The presence of plant diseases creates major difficulties for agricultural production that causes significant monetary damage while threatening food availability to populations. Machine ...
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

Plant Disease Detection System Using Convolutional Neural Networks: a Comprehensive Approach With Real-Time Deployment

Abstract: Early detection of plant diseases is vital for enhancing agricultural output and ensuring global food security. This paper introduces a robust and scalable Plant Disease Detection System ...
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, ...
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 ...