Deep learning for plant identification and disease classification from leaf images: multi-prediction approaches
Deep learning (DL) plays an important role in modern agriculture, especially in plant
pathology using leaf images where convolutional neural networks (CNN) are attracting a lot …
pathology using leaf images where convolutional neural networks (CNN) are attracting a lot …
Tomato plant disease classification using multilevel feature fusion with adaptive channel spatial and pixel attention mechanism
Agriculture's productivity has decreased in the last decade due to climate change and
inappropriate usage of water, fertilizer, and pesticides, which stimulate plant diseases. Plant …
inappropriate usage of water, fertilizer, and pesticides, which stimulate plant diseases. Plant …
Systematic study on deep learning-based plant disease detection or classification
Plant diseases impact extensively on agricultural production growth. It results in a price hike
on food grains and vegetables. To reduce economic loss and to predict yield loss, early …
on food grains and vegetables. To reduce economic loss and to predict yield loss, early …
Machine learning for leaf disease classification: data, techniques and applications
The growing demand for sustainable development brings a series of information
technologies to help agriculture production. Especially, the emergence of machine learning …
technologies to help agriculture production. Especially, the emergence of machine learning …
Affordable high throughput field detection of wheat stripe rust using deep learning with semi-automated image labeling
Stripe rust (caused by Puccinia striiformis f. sp. tritici) is one of the most devastating diseases
of wheat and causes large-scale epidemics and severe yield loss. Applying fungicides …
of wheat and causes large-scale epidemics and severe yield loss. Applying fungicides …
A meta-learning framework for recommending CNN models for plant disease identification tasks
Plant diseases are a major threat to food security and economic prosperity around the globe.
Deep learning models based on Convolution Neural Network (CNN) have shown promising …
Deep learning models based on Convolution Neural Network (CNN) have shown promising …
Binary class and multi-class plant disease detection using ensemble deep learning-based approach
Providing food for the exponentially growing global population is a highly challenging task.
Owing to the demand and supply gap may diminish food production due to diseases in …
Owing to the demand and supply gap may diminish food production due to diseases in …
“EffiNet-TS”: A deep interpretable architecture using EfficientNet for plant disease detection and visualization
M Gehlot, GC Gandhi - Journal of Plant Diseases and Protection, 2023 - Springer
Agriculture is crucial to the economy of any nation since it provides food and jobs for a
sizable percentage of the populace. However, plant diseases are one of the biggest …
sizable percentage of the populace. However, plant diseases are one of the biggest …
An efficient infectious disease detection in plants using deep learning
CK Sunil, CD Jaidhar - … , Applications, and Future Directions, Volume 3, 2024 - Springer
Over the past decade, agriculture has suffered reduced productivity from climate change and
improper water, fertilizer, and pesticide use, fueling plant diseases. Pathogens pose the …
improper water, fertilizer, and pesticide use, fueling plant diseases. Pathogens pose the …
LFMNet: a lightweight model for identifying leaf diseases of maize with high similarity
J Hu, X Jiang, J Gao, X Yu - Frontiers in Plant Science, 2024 - frontiersin.org
Maize leaf diseases significantly impact yield and quality. However, recognizing these
diseases from images taken in natural environments is challenging due to complex …
diseases from images taken in natural environments is challenging due to complex …