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Stereo Matching Algorithm Based On Per Pixel Difference Adjustment, Iterative Guided Filter And Graph Segmentation by Hamzah, Rostam Affendi, Ibrahim, Haidi, Abu Hassan, Anwar Hasni

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Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement by Kadmin, Ahmad Fauzan

“…Then, a new proposed cost aggregation based on the Hybrid Random Aggregation (HA) was implemented that utilized modified Iterative Non-Local Guided Filter (iNLGF), Simple Linear Iterative Clustering (SLIC), Graph Segmentation (GS) and Extended Restart Random Walk (eRWR) for error reduction. …”
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A maximal-clique-based clustering approach for multi-observer multi-view data by using k-nearest neighbor with S-pseudo-ultrametric induced by a fuzzy similarity by Khameneh, Azadeh Zahedi, Ghaznavi, Mehrdad, Kilicman, Adem, Mahad, Zahari, Mardani, Abbas

“…To this end, we first build a k-nearest neighbor (kNN) directed graph using the proposed S-distance, then transform it into an undirected graph based on the neighborhood information of the nodes so that the resultant graph is characterized based on nodes interactions and initial features information of the nodes. …”
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