51 citations · 131 across the 13 of their papers we have counts for
5 papers · 1 filter
Leveraging Random Label Memorization for Unsupervised Pre-Training
Vinaychandran Pondenkandath, Michele Alberti, Sammer Puran +2
We present a novel approach to leverage large unlabeled datasets by pre-training state-of-the-art deep neural networks on randomly-labeled datasets. Specifically, we train the neur…
Offline Signature Verification by Combining Graph Edit Distance and Triplet Networks
Paul Maergner, Vinaychandran Pondenkandath, Michele Alberti +4
Biometric authentication by means of handwritten signatures is a challenging pattern recognition task, which aims to infer a writer model from only a handful of genuine signatures.…
Are You Tampering With My Data?
Michele Alberti, Vinaychandran Pondenkandath, Marcel Würsch +4
We propose a novel approach towards adversarial attacks on neural networks (NN), focusing on tampering the data used for training instead of generating attacks on trained models. O…
DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments
Michele Alberti, Vinaychandran Pondenkandath, Marcel Würsch +2
We introduce DeepDIVA: an infrastructure designed to enable quick and intuitive setup of reproducible experiments with a large range of useful analysis functionality. Reproducing s…
Identifying Cross-Depicted Historical Motifs
Vinaychandran Pondenkandath, Michele Alberti, Nicole Eichenberger +2
Cross-depiction is the problem of identifying the same object even when it is depicted in a variety of manners. This is a common problem in handwritten historical documents image a…