A deep features extraction model based on the transfer learning model and vision transformer “tlmvit” for plant disease classification
A Tabbakh, SS Barpanda - IEEE Access, 2023 - ieeexplore.ieee.org
This paper proposes a novel approach for extracting deep features and classifying diseased
plant leaves. The agriculture industry is negatively impacted by plant diseases causing crop …
plant leaves. The agriculture industry is negatively impacted by plant diseases causing crop …
Automation of crop disease detection through conventional machine learning and deep transfer learning approaches
With the rapid population growth, increasing agricultural productivity is an extreme
requirement to meet demands. Early identification of crop diseases is essential to prevent …
requirement to meet demands. Early identification of crop diseases is essential to prevent …
Using deep transfer learning for image-based plant disease identification
Plant diseases have a disastrous impact on the safety of food production, and they can
cause a significant reduction in both the quality and quantity of agricultural products. In …
cause a significant reduction in both the quality and quantity of agricultural products. In …
A transfer learning-based artificial intelligence model for leaf disease assessment
The paddy crop is the most essential and consumable agricultural produce. Leaf disease
impacts the quality and productivity of paddy crops. Therefore, tackling this issue as early as …
impacts the quality and productivity of paddy crops. Therefore, tackling this issue as early as …
Optimized transfer learning approach for leaf disease classification in smart agriculture
In recent years, numerous deep learning architectures have used publicly available/author-
generated datasets to classify plant diseases. This study suggested a four-stage process for …
generated datasets to classify plant diseases. This study suggested a four-stage process for …
Multi-granularity feature extraction based on vision transformer for tomato leaf disease recognition
S Wu, Y Sun, H Huang - 2021 3rd International Academic …, 2021 - ieeexplore.ieee.org
At present, the task of identifying crop diseases is mainly to simply distinguish the types of
different crop diseases. However, the current classifiers cannot solve problems, such as …
different crop diseases. However, the current classifiers cannot solve problems, such as …
Inception convolutional vision transformers for plant disease identification
S Yu, L Xie, Q Huang - Internet of Things, 2023 - Elsevier
Plant disease has a considerable influence on the safety of grain output and quality.
Therefore, it is crucial to detect and diagnose plant diseases. Most plant diseases are …
Therefore, it is crucial to detect and diagnose plant diseases. Most plant diseases are …
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 …
[PDF][PDF] Towards Sustainable Agricultural Systems: A Lightweight Deep Learning Model for Plant Disease Detection.
A country's economy heavily depends on agricultural development. However, due to several
plant diseases, crop growth rate and quality are highly suffered. Accurate identification of …
plant diseases, crop growth rate and quality are highly suffered. Accurate identification of …
A deep learning based approach for automated plant disease classification using vision transformer
Plant disease can diminish a considerable portion of the agricultural products on each farm.
The main goal of this work is to provide visual information for the farmers to enable them to …
The main goal of this work is to provide visual information for the farmers to enable them to …