activity
20172023
most citedLeveraging Expert Models for Training Deep Neural Networks in Scarce Data Domains: Application to Offline Handwritten Signature Verification

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20233 cited

Leveraging Expert Models for Training Deep Neural Networks in Scarce Data Domains: Application to Offline Handwritten Signature Verification

Dimitrios Tsourounis, Ilias Theodorakopoulos, Elias N. Zois +1

This paper introduces a novel approach to leverage the knowledge of existing expert models for training new Convolutional Neural Networks, on domains where task-specific data are l…

cs.CV2018

A comprehensive study of sparse representation techniques for offline signature verification

Elias N. Zois, Dimitrios Tsourounis, Ilias Theodorakopoulos +2

In this work, a feature extraction method for offline signature verification is presented that harnesses the power of sparse representation in order to deliver state-of-the-art ver…

cs.CV2018

Attention-Aware Generative Adversarial Networks (ATA-GANs)

Dimitris Kastaniotis, Ioanna Ntinou, Dimitrios Tsourounis +2

In this work, we present a novel approach for training Generative Adversarial Networks (GANs). Using the attention maps produced by a Teacher- Network we are able to improve the qu…

cs.CV2017

3D Shape Classification Using Collaborative Representation based Projections

F. Fotopoulou, S. Oikonomou, A. Papathanasiou +2

A novel 3D shape classification scheme, based on collaborative representation learning, is investigated in this work. A data-driven feature-extraction procedure, taking the form of…

cs.CV2017

On the definition of Shape Parts: a Dominant Sets Approach

Foteini Fotopoulou, George Economou

In the present paper a novel graph-based approach to the shape decomposition problem is addressed. The shape is appropriately transformed into a visibility graph enriched with loca…