PND-Net: plant nutrition deficiency and disease classification using graph convolutional network
Crop yield production could be enhanced for agricultural growth if various plant nutrition
deficiencies, and diseases are identified and detected at early stages. Hence, continuous …
deficiencies, and diseases are identified and detected at early stages. Hence, continuous …
A comprehensive review of convolutional neural networks based disease detection strategies in potato agriculture
B Gülmez - Potato Research, 2024 - Springer
This review paper investigates the utilization of Convolutional Neural Networks (CNNs) for
disease detection in potato agriculture, highlighting their pivotal role in efficiently analyzing …
disease detection in potato agriculture, highlighting their pivotal role in efficiently analyzing …
An ensemble deep learning models approach using image analysis for cotton crop classification in AI-enabled smart agriculture
MF Shahid, TJS Khanzada, MA Aslam, S Hussain… - Plant methods, 2024 - Springer
Background Agriculture is one of the most crucial assets of any country, as it brings
prosperity by alleviating poverty, food shortages, unemployment, and economic instability …
prosperity by alleviating poverty, food shortages, unemployment, and economic instability …
[HTML][HTML] Crops Disease Detection, from Leaves to Field: What We Can Expect from Artificial Intelligence
Y Lebrini, A Ayerdi Gotor - Agronomy, 2024 - mdpi.com
Agriculture is dealing with numerous challenges of increasing production while decreasing
the amount of chemicals and fertilizers used. The intensification of agricultural systems has …
the amount of chemicals and fertilizers used. The intensification of agricultural systems has …
Enhancement of tea leaf diseases identification using modified SOTA models
KG Panchbhai, MG Lanjewar - Neural Computing and Applications, 2024 - Springer
The identification of tea leaf diseases holds considerable significance for preserving the
health of tea plants and preventing losses in tea production. This study introduced a hybrid …
health of tea plants and preventing losses in tea production. This study introduced a hybrid …
Potato harvesting prediction using an Improved ResNet-59 model
This paper highlights why it is crucial to determine crop production using artificial
intelligence for the growth of agriculture. In this paper, an elaborated ResNet-59 model has …
intelligence for the growth of agriculture. In this paper, an elaborated ResNet-59 model has …
A hybrid deep learning model for accurate potato leaf disease detection: Integration of U-Net and EfficientNetB7
SR Bogireddy, H Murari - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
Early detection and accurate classification of plant diseases are critical for enhancing crop
yield and ensuring food security. Traditional methods, while effective, often require manual …
yield and ensuring food security. Traditional methods, while effective, often require manual …
Maintaining Symmetry between Convolutional Neural Network Accuracy and Performance on an Edge TPU with a Focus on Transfer Learning Adjustments
Transfer learning has proven to be a valuable technique for deploying machine learning
models on edge devices and embedded systems. By leveraging pre-trained models and fine …
models on edge devices and embedded systems. By leveraging pre-trained models and fine …
Enhancing crop productivity with fined-tuned deep convolution neural network for Potato leaf disease detection
Potato plants (Solanum tuberosum) are prone to various diseases that result in substantial
economic losses for farmers. This research presents a deep learning-based approach to …
economic losses for farmers. This research presents a deep learning-based approach to …
Apnet: Lightweight network for apricot tree disease and pest detection in real-world complex backgrounds
Apricot trees, serving as critical agricultural resources, hold a significant role within the
agricultural domain. Conventional methods for detecting pests and diseases in these trees …
agricultural domain. Conventional methods for detecting pests and diseases in these trees …