116 citations · 117 across the 5 of their papers we have counts for
5 papers
UniMLR: Modeling Implicit Class Significance for Multi-Label Ranking
V. Bugra Yesilkaynak, Emine Dari, Alican Mertan +1
Existing multi-label ranking (MLR) frameworks only exploit information deduced from the bipartition of labels into positive and negative sets. Therefore, they do not benefit from r…
GaussianMLR: Learning Implicit Class Significance via Calibrated Multi-Label Ranking
V. Bugra Yesilkaynak, Emine Dari, Alican Mertan +1
Existing multi-label frameworks only exploit the information deduced from the bipartition of the labels into a positive and negative set. Therefore, they do not benefit from the ra…
RLSEP: Learning Label Ranks for Multi-label Classification
Emine Dari, V. Bugra Yesilkaynak, Alican Mertan +1
Multi-label ranking maps instances to a ranked set of predicted labels from multiple possible classes. The ranking approach for multi-label learning problems received attention for…
Symmetry and Variance: Generative Parametric Modelling of Historical Brick Wall Patterns
Sevgi Altun, Mustafa Cem Gunes, Yusuf H. Sahin +3
This study integrates artificial intelligence and computational design tools to extract information from architectural heritage. Photogrammetry-based point cloud models of brick wa…
Single Image Depth Estimation: An Overview
Alican Mertan, Damien Jade Duff, Gozde Unal
We review solutions to the problem of depth estimation, arguably the most important subtask in scene understanding. We focus on the single image depth estimation problem. Due to it…