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Showing results 1 to 5 of 5

1
A Convex Relaxation of the Ambrosio–Tortorelli Elliptic Functionals for the Mumford–Shah Functional

Kee, Youngwook; Kim, Junmo, CVPR 2014 IEEE conference on computer Vision and Pattern Recognition, IEEE Computer Society and the Computer Vision Foundation (CVF), 2014-06-24

2
Entropy minimization for convex relaxation approaches

Souiai, Mohamed; Oswald, Martin R; Kee, Youngwook; Kim, Junmo; Pollefeys, Marc; Cremers, Daniel, 15th IEEE International Conference on Computer Vision, ICCV 2015, pp.1778 - 1786, IEEE Computer Society and the Computer Vision Foundation (CVF), 2015-12

3
Groupwise Shape Registration Based on Entropy Minimization

Kee, Youngwook; Cremers, Daniel; Kim, Junmo, The German Association for Pattern Recognition and the Austrian Association for Pattern Recognition (DAGM-OAGM), pp.347 - 356, Techinical University Graz, 2012-08-29

4
Sequential Convex Relaxation for Mutual Information-Based Unsupervised Figure-Ground Segmentation

Kee, Youngwook; Mohamed Souiai; Daniel Cremers; Kim, Junmo, CVPR 2014 IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Society and the Computer Vision Foundation (CVF), 2014-06-24

5
Towards Flatter Loss Surface via Nonmonotonic Learning Rate Scheduling

Seong, Sihyeon; Lee, Yekang; Kee, Youngwook; Han, Dongyoon; Kim, Junmo, 34th Conference on Uncertainty in Artificial Intelligence (UAI), pp.1020 - 1030, Association for Uncertainty in Artificial Intelligence (AUAI), 2018-08-09

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