Explainable deep learning study for leaf disease classification
K Wei, B Chen, J Zhang, S Fan, K Wu, G Liu, D Chen - Agronomy, 2022 - mdpi.com
Explainable artificial intelligence has been extensively studied recently. However, the
research of interpretable methods in the agricultural field has not been systematically …
research of interpretable methods in the agricultural field has not been systematically …
[PDF][PDF] Explainable Deep Learning Models With Gradient-Weighted Class Activation Mapping for Smart Agriculture.
ABSTRACT Explainable Artificial Intelligence is a recent research direction that aims to
explain the results of the Deep learning model. However, many recent research need to go …
explain the results of the Deep learning model. However, many recent research need to go …
Improve the deep learning models in forestry based on explanations and expertise
In forestry studies, deep learning models have achieved excellent performance in many
application scenarios (eg, detecting forest damage). However, the unclear model decisions …
application scenarios (eg, detecting forest damage). However, the unclear model decisions …
Plant leaf disease detection using transfer learning and explainable ai
Among the major occupational sectors around the world, agriculture has the highest level of
involvement. Every year, this sector faces a substantial loss in production and profit due to a …
involvement. Every year, this sector faces a substantial loss in production and profit due to a …
Deep learning-based intelligent apple variety classification system and model interpretability analysis
F Yu, T Lu, C Xue - Foods, 2023 - mdpi.com
In this study, series networks (AlexNet and VGG-19) and directed acyclic graph (DAG)
networks (ResNet-18, ResNet-50, and ResNet-101) with transfer learning were employed to …
networks (ResNet-18, ResNet-50, and ResNet-101) with transfer learning were employed to …
Explainable deep learning model for automatic mulberry leaf disease classification
Mulberry leaves feed Bombyx mori silkworms to generate silk thread. Diseases that affect
mulberry leaves have reduced crop and silk yields in sericulture, which produces 90% of the …
mulberry leaves have reduced crop and silk yields in sericulture, which produces 90% of the …
Usefulness of interpretability methods to explain deep learning based plant stress phenotyping
Deep learning techniques have been successfully deployed for automating plant stress
identification and quantification. In recent years, there is a growing push towards training …
identification and quantification. In recent years, there is a growing push towards training …
Explainable vision transformer enabled convolutional neural network for plant disease identification: PlantXViT
Plant diseases are the primary cause of crop losses globally, with an impact on the world
economy. To deal with these issues, smart agriculture solutions are evolving that combine …
economy. To deal with these issues, smart agriculture solutions are evolving that combine …
Tomato leaf disease diagnosis based on improved convolution neural network by attention module
S Zhao, Y Peng, J Liu, S Wu - Agriculture, 2021 - mdpi.com
Crop disease diagnosis is of great significance to crop yield and agricultural production.
Deep learning methods have become the main research direction to solve the diagnosis of …
Deep learning methods have become the main research direction to solve the diagnosis of …
Enhancing crop productivity through autoencoder-based disease detection and context-aware remedy recommendation system
According to experts, recent developments in agricultural sectors are inherently connected
to the production and all other facets of agriculture to increase crop productivity. The most …
to the production and all other facets of agriculture to increase crop productivity. The most …