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Identification of Cotton Leaf Lesions Using Deep Learning Techniques
- Source :
- Sensors, Vol 21, Iss 3169, p 3169 (2021), Sensors, Volume 21, Issue 9, Sensors (Basel, Switzerland)
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- The use of deep learning models to identify lesions on cotton leaves on the basis of images of the crop in the field is proposed in this article. Cultivated in most of the world, cotton is one of the economically most important agricultural crops. Its cultivation in tropical regions has made it the target of a wide spectrum of agricultural pests and diseases, and efficient solutions are required. Moreover, the symptoms of the main pests and diseases cannot be differentiated in the initial stages, and the correct identification of a lesion can be difficult for the producer. To help resolve the problem, the present research provides a solution based on deep learning in the screening of cotton leaves which makes it possible to monitor the health of the cotton crop and make better decisions for its management. With the learning models GoogleNet and Resnet50 using convolutional neural networks, a precision of 86.6% and 89.2%, respectively, was obtained. Compared with traditional approaches for the processing of images such as support vector machines (SVM), Closest k-neighbors (KNN), artificial neural networks (ANN) and neuro-fuzzy (NFC), the convolutional neural networks proved to be up to 25% more precise, suggesting that this method can contribute to a more rapid and reliable inspection of the plants growing in the field.
- Subjects :
- Support Vector Machine
Computer science
Image processing
TP1-1185
02 engineering and technology
Machine learning
computer.software_genre
Biochemistry
Convolutional neural network
Article
Field (computer science)
Analytical Chemistry
Deep Learning
convolutional neural networks
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
Instrumentation
precision agriculture
Artificial neural network
business.industry
Chemical technology
Deep learning
04 agricultural and veterinary sciences
artificial intelligence
Atomic and Molecular Physics, and Optics
image processing
Plant Leaves
Support vector machine
Identification (information)
040103 agronomy & agriculture
0401 agriculture, forestry, and fisheries
020201 artificial intelligence & image processing
Neural Networks, Computer
Precision agriculture
Artificial intelligence
business
computer
Algorithms
Subjects
Details
- ISSN :
- 14248220
- Volume :
- 21
- Database :
- OpenAIRE
- Journal :
- Sensors
- Accession number :
- edsair.doi.dedup.....f4e58f2483db8ce77132b4f35eefc3e3