A benchmarking: Feature extraction and classification of agricultural textures using LBP, GLCM, RBO, Neural Networks, k-NN, and random forest.
Sercan AygunEce Olcay GünesPublished in: Agro-Geoinformatics (2017)
Keyphrases
- random forest
- knn
- feature extraction and classification
- texture features
- texture classification
- neural network
- feature set
- local binary pattern
- k nearest neighbor
- feature extraction
- texture analysis
- texture descriptors
- feature selection
- nearest neighbor
- pattern recognition
- feature vectors
- gabor filters
- gray level
- text categorization
- decision trees
- support vector machine svm
- nearest neighbour
- text classification
- ensemble learning
- multi label
- ensemble methods
- artificial neural networks
- face recognition
- distance measure
- image features
- support vector machine
- feature space
- ensemble classifier
- kernel function
- principal component analysis
- multiscale
- vehicle detection
- graph cuts
- feature subset
- unsupervised learning
- multi class
- high dimensional
- training data
- data mining