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Decision tree induction using a fast splitting attribute selection for large datasets
(Elsevier Ltd., 2011)
A fast and low-cost method to detect nearduplicate Images in large dataset based on fingerprint extraction and Deep Learning
(Biblioteca Digital wdg.biblioUniversidad de Guadalajara, 2023-03-16)
Recognizing near-duplicate images from large datasets is a crucial task in image retrieval
and content identification. Finding similar images in order to reduce redundancy is timeconsuming in large datasets. Most of image ...
Assessing the effective sample size for large spatial datasets: A block likelihood approach
(2021)
The development of new techniques for sample size reduction has attracted growing interest in recent decades. Recent findings allow us to quantify the amount of duplicated information within a sample of spatial data through ...
Efficient supervised optimum-path forest classification for large datasets
(Elsevier B.V., 2012-01-01)
Today data acquisition technologies come up with large datasets with millions of samples for statistical analysis. This creates a tremendous challenge for pattern recognition techniques, which need to be more efficient ...
Efficient supervised optimum-path forest classification for large datasets
(Elsevier B.V., 2012-01-01)
Today data acquisition technologies come up with large datasets with millions of samples for statistical analysis. This creates a tremendous challenge for pattern recognition techniques, which need to be more efficient ...
Improving the accuracy of the optimum-path forest supervised classifier for large datasets
(2010-12-15)
In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the ...