End-to-End Deep Learning Model for Corn Leaf Disease Classification
Helwan University · Scientific Research Group in Egypt · +1 more institution
Abstract
Plant diseases compose a great threat to global food security. However, the rapid identification of plant diseases remains challenging and time-consuming. It requires experts to accurately identify if the plant is healthy or not and identify the type of infection. Deep learning techniques have recently been used to identify and diagnose diseased plants from digital images to help automate plant disease diagnosis and help non-experts identify diseased plants. While many deep learning applications have been used to identify diseased plants and aims to increase the detection rate, the limitation of the large parameter size in the models persist. In this paper, an end-to-end deep learning model is developed to…
Citation impact
- FWCI
- 46.82
- Percentile
- 100%
- References
- 24
Authors
4Topics & keywords
- Deep learning
- Artificial intelligence
- Convolutional neural network
- Computer science
- Plant disease
- Machine learning
- Concatenation (mathematics)
- Pattern recognition (psychology)
- Zero hunger