Panagiotis Stanitsas — accepted AI-conference papers

2017

Learning Discriminative ab-Divergences for Positive Definite Matrices

Anoop Cherian, Panagiotis Stanitsas, Mehrtash Harandi, Vassilios Morellas, Nikolaos Papanikolopoulos

ICCV 2017poster

Symmetric positive definite (SPD) matrices are useful for capturing second-order statistics of visual data. To compare two SPD matrices, several measures are available, such as the affine-invariant Riemannian metric, Jeffreys divergence, Jensen-Bregman logdet divergence, etc.; however, their behavio…

Cited by 6 PDF ↗Scholar ↗

2016

Active Constrained Clustering via non-iterative uncertainty sampling

Panagiotis Stanitsas, Anoop Cherian, Vassilios Morellas, Nikolaos Papanikolopoulos

IROS 2016poster

Active Constraint Learning (ACL) is continuously gaining popularity in the area of constrained clustering due to its ability to achieve performance gains via incorporating minimal feedback from a human annotator for selected instances. For constrained clustering algorithms, such instances are integr…

Cited by 4 Source ↗Scholar ↗

2015

Automation solutions for the evaluation of plant health in corn fields

Dimitris Zermas, Da Teng, Panagiotis Stanitsas, Michael Bazakos, Daniel Kaiser, Vassilios Morellas +2

IROS 2015poster

The continuously growing need for increasing the production of food and reducing the degradation of water supplies, has led to the development of several precision agriculture systems over the past decade so as to meet the needs of modern societies. The present study describes a methodology for the…

Cited by 41 Source ↗Scholar ↗