High-degree noise addition method for the $k$-degree anonymization algorithm.
Jana MedkováPublished in: SCIS/ISIS (2020)
Keyphrases
- dynamic programming
- significant improvement
- cost function
- noisy data
- detection algorithm
- experimental evaluation
- high accuracy
- detection method
- clustering method
- high efficiency
- synthetic and real images
- preprocessing
- information loss
- improved algorithm
- convergence rate
- matching algorithm
- energy function
- segmentation method
- classification method
- computationally efficient
- input data
- single pass
- theoretical analysis
- estimation algorithm
- computational cost
- objective function
- support vector machine svm
- segmentation algorithm
- recognition algorithm
- k means
- noise free
- noise immunity
- optimization algorithm
- probabilistic model
- learning algorithm
- single parameter
- similarity measure
- selection algorithm
- em algorithm
- expectation maximization
- computational complexity
- classification algorithm
- filtering method
- tree structure
- optimization method
- graph cuts
- support vector machine
- reconstruction method
- optimal solution
- noise sensitivity