Revolutionizing Maize Disease Management with Federated Learning CNNs: A Decentralized and Privacy-Sensitive Approach
For sustainable maize production, reliable and prompt disease identification is crucial.
Maize diseases represent a danger to world food security. In this work, utilizing …
Maize diseases represent a danger to world food security. In this work, utilizing …
From conventional approach to machine learning and deep learning approach: an experimental and comprehensive review of image fusion techniques
G Choudhary, D Sethi - Archives of Computational Methods in …, 2023 - Springer
Images captured from a single or multiple imaging sensors with considerable focus or
numerous exposures of the same or different modalities do not provide all relevant …
numerous exposures of the same or different modalities do not provide all relevant …
Exploring the Potential of Convolutional Neural Networks in Automatic Diagnosis of Dragon Fruit Diseases from Plant Photographs
Numerous instances of dragon fruit diseases over the years have caused an estimated 14%
annual crop loss globally, affecting untold millions of people. The study of dragon fruit …
annual crop loss globally, affecting untold millions of people. The study of dragon fruit …
BC2NetRF: Breast Cancer Classification from Mammogram Images Using Enhanced Deep Learning Features and Equilibrium-Jaya Controlled Regula Falsi-Based …
One of the most frequent cancers in women is breast cancer, and in the year 2022,
approximately 287,850 new cases have been diagnosed. From them, 43,250 women died …
approximately 287,850 new cases have been diagnosed. From them, 43,250 women died …
Next-Generation Wheat Disease Monitoring: Leveraging Federated Convolutional Neural Networks for Severity Estimation
In this study, we investigate using federated learning for the CNN model-based prediction of
wheat disease severity levels. We employed safe aggregation approaches to training the …
wheat disease severity levels. We employed safe aggregation approaches to training the …
Optimized stacking ensemble learning model for breast cancer detection and classification using machine learning
Breast cancer is the most frequently encountered medical hazard for women in their forties,
affecting one in every eight women. It is the greatest cause of death worldwide, and early …
affecting one in every eight women. It is the greatest cause of death worldwide, and early …
Empowering Farmers with AI: Federated Learning of CNNs for Wheat Diseases Multi-Classification
Higher agricultural outputs are required due to the rising worldwide population, shifting
nutritional preferences, and growing demand for food and basic materials for the industry …
nutritional preferences, and growing demand for food and basic materials for the industry …
Transforming Agriculture: Federated Learning CNNs for Wheat Disease Severity Assessment
It is crucial to correctly identify and evaluate wheat illnesses to stop their growth and boost
farming output. This research study intends to use CNN with collaborative learning to …
farming output. This research study intends to use CNN with collaborative learning to …
Precision Agriculture: Classifying Banana Leaf Diseases with Hybrid Deep Learning Models
The majority of the people in India dependent on farming to earn a living. As a due to climate
change, farmers face various challenges. One of them is a reduction in yield, and one of the …
change, farmers face various challenges. One of them is a reduction in yield, and one of the …
Combining transformers with CNN for multi-focus image fusion
Z Duan, X Luo, T Zhang - Expert Systems with Applications, 2024 - Elsevier
Recently, deep convolutional neural network (CNN) based methods for multi-focus image
fusion have achieved adequate performance. However, most of them cannot obtain spatially …
fusion have achieved adequate performance. However, most of them cannot obtain spatially …