Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...
Abstract: Agricultural productivity is helpless against various diseases that result in significant losses in terms of resources. These losses rise rapidly in isolated locations with limited resources ...
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 ...
Abstract: The agricultural economy all around the world is controlled by citrus fruits. Nevertheless, the presence of a number of plant diseases, which are often difficult to detect in an early stage, ...
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 ...
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 ...
Abstract: In a country like India, where agriculture provides for both nationwide consumption and merchandise exports, plant disease is one of the most significant factors that might impact crop ...
Abstract: This research paper introduces a new hybrid method that combines Convolutional Neural Network (CNN) with Support Vector Machine (SVM) algorithms for the automated detection of apple leaf ...
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, ...