Machine learning in agriculture: A comprehensive updated review
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …
artificial intelligent systems for the sake of making value from the ever-increasing data …
A revisit of internet of things technologies for monitoring and control strategies in smart agriculture
With the rise of new technologies, such as the Internet of Things, raising the productivity of
agricultural and farming activities is critical to improving yields and cost-effectiveness. IoT, in …
agricultural and farming activities is critical to improving yields and cost-effectiveness. IoT, in …
Early detection and classification of tomato leaf disease using high-performance deep neural network
Tomato is one of the most essential and consumable crops in the world. Tomatoes differ in
quantity depending on how they are fertilized. Leaf disease is the primary factor impacting …
quantity depending on how they are fertilized. Leaf disease is the primary factor impacting …
Plant image recognition with deep learning: A review
Y Chen, Y Huang, Z Zhang, Z Wang, B Liu, C Liu… - … and Electronics in …, 2023 - Elsevier
Significant advances in the field of digital image processing have been achieved in recent
years using deep learning, which has significantly exceeded previous methods. Deep …
years using deep learning, which has significantly exceeded previous methods. Deep …
Meta deep learn leaf disease identification model for cotton crop
Agriculture is essential to the growth of every country. Cotton and other major crops fall into
the cash crops. Cotton is affected by most of the diseases that cause significant crop …
the cash crops. Cotton is affected by most of the diseases that cause significant crop …
A transfer residual neural network based on ResNet-34 for detection of wood knot defects
M Gao, D Qi, H Mu, J Chen - Forests, 2021 - mdpi.com
In recent years, due to the shortage of timber resources, it has become necessary to reduce
the excessive consumption of forest resources. Non-destructive testing technology can …
the excessive consumption of forest resources. Non-destructive testing technology can …
A forest fire recognition method using UAV images based on transfer learning
L Zhang, M Wang, Y Fu, Y Ding - Forests, 2022 - mdpi.com
Timely detection of forest wildfires is of great significance to the early prevention and control
of large-scale forest fires. Unmanned Aerial Vehicle (UAV) with cameras has the …
of large-scale forest fires. Unmanned Aerial Vehicle (UAV) with cameras has the …
Intelligent plant disease diagnosis using convolutional neural network: a review
In recent times use of different technologies for intelligent crop production is growing. To
increase the production of crops, diagnosing a plant disease is very important. Plant …
increase the production of crops, diagnosing a plant disease is very important. Plant …
Efficient identification of apple leaf diseases in the wild using convolutional neural networks
Q Yang, S Duan, L Wang - Agronomy, 2022 - mdpi.com
Efficient identification of apple leaf diseases (ALDs) can reduce the use of pesticides and
increase the quality of apple fruit, which is of significance to smart agriculture. However …
increase the quality of apple fruit, which is of significance to smart agriculture. However …
Apple-Net: A model based on improved YOLOv5 to detect the apple leaf diseases
R Zhu, H Zou, Z Li, R Ni - Plants, 2022 - mdpi.com
Effective identification of apple leaf diseases can reduce pesticide spraying and improve
apple fruit yield, which is significant to agriculture. However, the existing apple leaf disease …
apple fruit yield, which is significant to agriculture. However, the existing apple leaf disease …