A survey on using deep learning techniques for plant disease diagnosis and recommendations for development of appropriate tools
Several factors associated with disease diagnosis in plants using deep learning techniques
must be considered to develop a robust system for accurate disease management. A …
must be considered to develop a robust system for accurate disease management. A …
Machine learning for detection and prediction of crop diseases and pests: A comprehensive survey
Considering the population growth rate of recent years, a doubling of the current worldwide
crop productivity is expected to be needed by 2050. Pests and diseases are a major …
crop productivity is expected to be needed by 2050. Pests and diseases are a major …
Artificial intelligence-based drone system for multiclass plant disease detection using an improved efficient convolutional neural network
The role of agricultural development is very important in the economy of a country. However,
the occurrence of several plant diseases is a major hindrance to the growth rate and quality …
the occurrence of several plant diseases is a major hindrance to the growth rate and quality …
Climate change effects on pathogen emergence: Artificial intelligence to translate big data for mitigation
Plant pathology has developed a wide range of concepts and tools for improving plant
disease management, including models for understanding and responding to new risks from …
disease management, including models for understanding and responding to new risks from …
DiaMOS plant: A dataset for diagnosis and monitoring plant disease
G Fenu, FM Malloci - Agronomy, 2021 - mdpi.com
The classification and recognition of foliar diseases is an increasingly develo** field of
research, where the concepts of machine and deep learning are used to support agricultural …
research, where the concepts of machine and deep learning are used to support agricultural …
Biostimulant and antagonistic potential of endophytic fungi against fusarium wilt pathogen of tomato Fusarium oxysporum f. sp. lycopersici
Endophytic fungal-based biopesticides are sustainable and ecologically-friendly biocontrol
agents of several pests and diseases. However, their potential in managing tomato fusarium …
agents of several pests and diseases. However, their potential in managing tomato fusarium …
Machine learning for plant stress modeling: A perspective towards hormesis management
Plant stress is one of the most significant factors affecting plant fitness and, consequently,
food production. However, plant stress may also be profitable since it behaves hormetically; …
food production. However, plant stress may also be profitable since it behaves hormetically; …
Application of image processing and transfer learning for the detection of rust disease
Plant diseases introduce significant yield and quality losses to the food production industry,
worldwide. Early identification of an epidemic could lead to more effective management of …
worldwide. Early identification of an epidemic could lead to more effective management of …
Using multioutput learning to diagnose plant disease and stress severity
G Fenu, FM Malloci - Complexity, 2021 - Wiley Online Library
Early diagnosis of leaf diseases is a fundamental tool in precision agriculture, thanks to its
high correlation with food safety and environmental sustainability. It is proven that plant …
high correlation with food safety and environmental sustainability. It is proven that plant …
Classification of pear leaf diseases based on ensemble convolutional neural networks
G Fenu, FM Malloci - AgriEngineering, 2023 - mdpi.com
Over the last few years, the impact of climate change has increased rapidly. It is influencing
all steps of plant production and forcing farmers to change and adapt their crop …
all steps of plant production and forcing farmers to change and adapt their crop …