Coarse Clustering and Classification of Images with CNN Features for Participatory Sensing in Agriculture.
Prakruti BhattSanat SarangiSrinivasu PappulaPublished in: ICPRAM (2018)
Keyphrases
- extracted features
- extracting features
- image features
- image classification
- correct classification rate
- feature extraction
- discriminative features
- visual object recognition
- classification accuracy
- original images
- feature vectors
- feature representation
- feature set
- individual features
- multiple classifiers
- test images
- classification models
- handwritten digits
- image data
- image retrieval
- image database
- high dimensionality
- feature space
- class specific
- classification method
- gabor filters
- skin lesion
- object recognition
- feature descriptors
- som neural network
- textural features
- svm classifier
- class labels
- edge detection
- fisher linear discriminant
- convolutional neural network
- support vector
- decision trees
- supervised learning
- clustering algorithm
- image analysis
- k means
- support vector machine
- input image
- clustering method
- image matching
- coarse to fine
- keypoints
- discriminative classifiers
- image regions
- low level
- spatial information
- image set
- unsupervised learning
- feature points
- multiresolution
- gray level co occurrence matrix