Grassmannian Dimensionality Reduction Using Triplet Margin Loss for Ume Classification of 3d Point Clouds.
Yuval HaitmanJoseph M. FrancosLouis L. ScharfPublished in: ICASSP (2022)
Keyphrases
- dimensionality reduction
- support vector
- high dimensionality
- feature extraction
- feature selection
- decision trees
- pattern recognition
- training set
- classification accuracy
- feature space
- pattern recognition and machine learning
- support vector machine svm
- high dimensional data
- subspace learning
- pattern classification
- text classification
- dimensionality reduction methods
- decision boundary
- point cloud
- structure preserving
- low dimensional
- classification method
- classification algorithm
- nearest neighbor
- support vector machine
- feature vectors
- neural network
- class labels
- structure from motion
- data sets
- principal component analysis
- supervised learning
- data representation
- generalization error
- image processing