Search Results for author: Bernhard Bermeitinger

Found 9 papers, 0 papers with code

Training Neural Networks in Single vs Double Precision

no code implementations15 Sep 2022 Tomas Hrycej, Bernhard Bermeitinger, Siegfried Handschuh

For strongly nonlinear tasks, both algorithm classes find only solutions fairly poor in terms of mean square error as related to the output variance.

Number of Attention Heads vs Number of Transformer-Encoders in Computer Vision

no code implementations15 Sep 2022 Tomas Hrycej, Bernhard Bermeitinger, Siegfried Handschuh

Determining an appropriate number of attention heads on one hand and the number of transformer-encoders, on the other hand, is an important choice for Computer Vision (CV) tasks using the Transformer architecture.

Multimodal Semantic Transfer from Text to Image. Fine-Grained Image Classification by Distributional Semantics

no code implementations7 Jan 2020 Simon Donig, Maria Christoforaki, Bernhard Bermeitinger, Siegfried Handschuh

In the last years, image classification processes like neural networks in the area of art-history and Heritage Informatics have experienced a broad distribution (Lang and Ommer 2018).

Fine-Grained Image Classification General Classification

Representational Capacity of Deep Neural Networks -- A Computing Study

no code implementations19 Jul 2019 Bernhard Bermeitinger, Tomas Hrycej, Siegfried Handschuh

This does not directly contradict the theoretical findings---it is possible that the superior representational capacity of deep networks is genuine while finding the mean square minimum of such deep networks is a substantially harder problem than with shallow ones.

Singular Value Decomposition and Neural Networks

no code implementations27 Jun 2019 Bernhard Bermeitinger, Tomas Hrycej, Siegfried Handschuh

Singular Value Decomposition (SVD) constitutes a bridge between the linear algebra concepts and multi-layer neural networks---it is their linear analogy.

Object Classification in Images of Neoclassical Artifacts Using Deep Learning

no code implementations13 Oct 2017 Bernhard Bermeitinger, Maria Christoforaki, Simon Donig, Siegfried Handschuh

In this paper, we report on our efforts for using Deep Learning for classifying artifacts and their features in digital visuals as a part of the Neoclassica framework.

Classification General Classification

A Sentence Simplification System for Improving Relation Extraction

no code implementations COLING 2016 Christina Niklaus, Bernhard Bermeitinger, Siegfried Handschuh, André Freitas

In this demo paper, we present a text simplification approach that is directed at improving the performance of state-of-the-art Open Relation Extraction (RE) systems.

Relation Extraction Text Simplification

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