An Efficient Plant Disease Recognition System Using Hybrid Convolutional Neural Networks (CNNs) and Conditional Random Fields (CRFs) for Smart IoT Applications in Agriculture.
Nermeen Gamal RezkAbdel-Fattah AttiaMohamed A. El-RashidyAyman El-SayedEzz El-Din HemdanPublished in: Int. J. Comput. Intell. Syst. (2022)
Keyphrases
- conditional random fields
- convolutional neural networks
- hidden markov models
- crf model
- sequence labeling
- graphical models
- higher order
- markov random field
- probabilistic model
- information extraction
- maximum entropy
- random fields
- image labeling
- markov models
- generative model
- markov networks
- structured prediction
- pairwise
- parameter learning
- contextual features
- feature extraction
- semi markov
- undirected graphical models
- approximate inference
- superpixels
- fully connected
- structured learning
- image processing
- dynamic conditional random fields
- semantic segmentation
- segmentation method
- structured domains
- web page prediction