Comparison of Deep Learning Approaches for Plant Disease Detection
To make agriculture produce better results, several disease detection methods can be used to detect the diseased plant and take on some precautionary measures. Based on recent paper reviews, disease detection can be a very lengthy and complex job. The detection of disease still remains open for more modification and detects the disease with more accuracy and efficiency. Use of CNN (Convolutional Neural Network) models with deep learning methodologies have provided a boon to plant disease detection.
KeywordsDeep learning Convolution neural networks with ALEXNET VGG and inception
- 1.Hughes D, Salathé M (2015) An open access repository of images on plant health to enable the development of mobile disease diagnostics. arXiv preprint arXiv:1511.08060
- 2.Simonyan K, Vedaldi A, Zisserman A (2013) Deep inside convolutional networks: visualising image classification models and saliency maps. arxiv preprint arxiv:1312.6034Google Scholar
- 3.Sladojevic S et al (2016) Deep neural networks based recognition of plant diseases by leaf image classification. Comput Intell NeurosciGoogle Scholar
- 5.Atabay HA (2017) Deep residual learning for tomato plant leaf disease identification. J Theor Appl Inf Technol 95(24)Google Scholar