NUBF correction methods for the GPM/DPR level-2 algorithms.
Shinta SetoToshio IguchiTatsuya ShimozumaShota HayashiPublished in: IGARSS (2015)
Keyphrases
- computational cost
- benchmark datasets
- methods require
- computationally intensive
- significant improvement
- computer vision algorithms
- computationally expensive
- data mining techniques
- computationally demanding
- image processing algorithms
- machine learning methods
- efficient implementation
- search methods
- heuristic methods
- data structure
- mathematical models
- synthetic and real data sets
- methods outperform
- machine learning
- preprocessing
- machine learning algorithms
- theoretical analysis
- classical methods
- algorithms require
- problems in computer vision
- experimental comparison
- efficient optimization
- alternative methods
- complexity analysis
- graph theory
- learning models
- optimization methods
- statistical methods
- computationally efficient
- empirical studies
- optimization problems
- worst case
- computational complexity