K-Means system and SIFT algorithm as a faster and more efficient solution for the detection of pulmonary tuberculosis.
Luis M. Ortega MelgarejoHugo David Calderon-VilcaGuido Raul Larico UchamacoFlor Cagniy Cárdenas MariñoPublished in: Computación y Sistemas (2020)
Keyphrases
- k means
- detection algorithm
- single pass
- cost function
- learning algorithm
- memory efficient
- computational complexity
- optimal solution
- highly efficient
- detection method
- preprocessing
- matching algorithm
- solution quality
- data clustering
- cluster analysis
- closed form
- image matching
- mathematical model
- clustering method
- optimization algorithm
- hierarchical clustering
- expectation maximization
- high efficiency
- np hard
- spectral clustering
- similarity measure
- detection rate
- clustering algorithm
- region of interest
- keypoints
- objective function
- segmentation algorithm
- computationally efficient
- particle swarm optimization
- linear programming
- worst case
- computational cost