AIMC Topic: Plant Diseases

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Deep learning system for paddy plant disease detection and classification.

Environmental monitoring and assessment
Automatic detection and analysis of rice crop diseases is widely required in the farming industry, which can be utilized to avoid squandering financial and other resources, reduce yield losses, and improve treatment efficiency, resulting in healthier...

A robust deep learning approach for tomato plant leaf disease localization and classification.

Scientific reports
Tomato plants' disease detection and classification at the earliest stage can save the farmers from expensive crop sprays and can assist in increasing the food quantity. Although, extensive work has been presented by the researcher for the tomato pla...

An Improved Deep Residual Convolutional Neural Network for Plant Leaf Disease Detection.

Computational intelligence and neuroscience
In this research, we proposed a novel deep residual convolutional neural network with 197 layers (ResNet197) for the detection of various plant leaf diseases. Six blocks of layers were used to develop ResNet197. ResNet197 was trained and tested using...

A deep learning based approach for automated plant disease classification using vision transformer.

Scientific reports
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 take the necessary preventive measures. A lightweight deep lear...

Classification of Citrus Diseases Using Optimization Deep Learning Approach.

Computational intelligence and neuroscience
Most plant diseases have apparent signs, and today's recognized method is for an expert plant pathologist to identify the disease by looking at infected plant leaves using a microscope. The fact is that manually diagnosing diseases is time consuming ...

Detection and identification of tea leaf diseases based on AX-RetinaNet.

Scientific reports
The accurate detection and identification of tea leaf diseases are conducive to its precise prevention and control. Convolutional neural network (CNN) can automatically extract the features of diseased tea leaves in the images. However, tea leaf imag...

A method of detecting apple leaf diseases based on improved convolutional neural network.

PloS one
Apple tree diseases have perplexed orchard farmers for several years. At present, numerous studies have investigated deep learning for fruit and vegetable crop disease detection. Because of the complexity and variety of apple leaf veins and the diffi...

Modeling risk of Sclerotinia sclerotiorum-induced disease development on canola and dry bean using machine learning algorithms.

Scientific reports
Diseases caused by the fungus Sclerotinia sclerotiorum are managed mainly through fungicide applications in canola and dry bean. Accurate estimation of the risk of disease development on these crops could help farmers make spraying decisions. Five ma...

Recognition of Leaf Disease Using Hybrid Convolutional Neural Network by Applying Feature Reduction.

Sensors (Basel, Switzerland)
Agriculture is crucial to the economic prosperity and development of India. Plant diseases can have a devastating influence towards food safety and a considerable loss in the production of agricultural products. Disease identification on the plant is...

Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease.

Nature communications
Medicines and agricultural biocides are often discovered using large phenotypic screens across hundreds of compounds, where visible effects of whole organisms are compared to gauge efficacy and possible modes of action. However, such analysis is ofte...