Πλοήγηση ανά Θέμα "Experimental comparison"

Algorithms for processing the group K nearest-neighbor query on distributed frameworks

Moutafis P., García-García F., Mavrommatis G., Vassilakopoulos M., Corral A., Iribarne L. (2021)

Given two datasets of points (called Query and Training), the Group (K) Nearest-Neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum of distances to every point of the Query. This spatial query ...

Bimodal CT/MRI-based segmentation method for intervertebral disc boundary extraction

Liaskos M., Savelonas M.A., Asvestas P.A., Lykissas M.G., Matsopoulos G.K. (2020)

Intervertebral disc (IVD) localization and segmentation have triggered intensive research efforts in the medical image analysis community, since IVD abnormalities are strong indicators of various spinal cord-related ...

Bulk insertions into xBR+-trees

Roumelis G., Vassilakopoulos M., Corral A., Manolopoulos Y. (2017)

Bulk insertion refers to the process of updating an existing index by inserting a large batch of new data, treating the items of this batch as a whole and not by inserting these items one-by-one. Bulk insertion is related ...

Bulk-loading xBR+-trees

Roumelis G., Vassilakopoulos M., Corral A., Manolopoulos Y. (2016)

Spatial indexes are important in spatial databases for efficient execution of queries involving spatial constraints. The xBR+-tree is a balanced disk-resident quadtree-based index structure for point data, which is very ...

In-memory k nearest neighbor GPU-based query processing

Velentzas P., Vassilakopoulos M., Corral A. (2020)

The k Nearest Neighbor (k-NN) algorithm is widely used for classification in several application domains (medicine, economy, entertainment, etc.). Let a group of query points, for each of which we need to compute the k-NNs ...