Combing modified Grabcut, K-means clustering and sparse representation classification for weed recognition in wheat field.
Shanwen ZhangWenzhun HuangZuliang WangPublished in: Neurocomputing (2021)
Keyphrases
- sparse representation
- dictionary learning
- image classification
- pattern recognition
- sparse coding
- feature extraction
- compressed sensing
- face recognition
- compressive sensing
- unsupervised learning
- sparse approximations
- image representation
- random projections
- dimensionality reduction
- signal processing
- joint optimization
- object tracking
- sparse reconstruction
- negative matrix factorization
- regularized least squares
- natural images
- feature vectors
- object recognition
- decision trees
- action recognition
- feature space
- support vector
- feature selection
- text classification
- image patches
- supervised learning
- support vector machine
- training set
- multiscale
- sparsity constraints
- clustering algorithm