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Computer Science

D-Index
38
Citations
6869
World Ranking
10158
National Ranking
508

Overview

Erhardt Barth is affiliated with the University of Lübeck in Germany. Their research primarily spans the fields of Computer Science and Medicine, with specific contributions in Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Signal Processing, and Electrical and Electronic Engineering.

Their work addresses several main research topics, including Advanced Neural Network Applications, COVID-19 diagnosis using AI, Radiomics and Machine Learning in Medical Imaging, Human Pose and Action Recognition, Biometric Identification and Security, Face Recognition and Analysis, and Anomaly Detection Techniques and Applications.

Erhardt Barth has published recent papers that include the following titles:

  • "Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning" (2021) in Sensors
  • "Deep Convolutional Neural Networks for Unconstrained Ear Recognition" (2020) in IEEE Access
  • "COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans" (2021) in PeerJ Computer Science
  • "Towards Explainable Ear Recognition Systems Using Deep Residual Networks" (2021) in IEEE Access
  • "COVID-Nets: Deep CNN Architectures for Detecting COVID-19 Using Chest CT Scans" (2021) in bioRxiv (Cold Spring Harbor Laboratory)

Frequent co-authors collaborating with Erhardt Barth include:

  • Thomas Martinetz
  • Philipp Grüning
  • Hammam Alshazly
  • Christoph Linse
  • Yaxin Hu

Common publication venues for Barth's research consist of:

  • arXiv (Cornell University)
  • IEEE Access
  • Journal of Perceptual Imaging
  • Sensors
  • PeerJ Computer Science

Best Publications

  • Time-of-Flight Cameras in Computer Graphics

    Andreas Kolb;Erhardt Barth;Reinhard Koch;Rasmus Larsen

  • Variability of eye movements when viewing dynamic natural scenes.

    Michael Dorr;Thomas Martinetz;Karl R. Gegenfurtner;Erhardt Barth

  • A Multi-Organ Nucleus Segmentation Challenge

    Neeraj Kumar;Ruchika Verma;Deepak Anand;Yanning Zhou

  • ACCURATE EYE CENTRE LOCALISATION BY MEANS OF GRADIENTS

    Fabian Timm;Erhardt Barth

  • Time-of-Flight Sensors in Computer Graphics

    Andreas Kolb;Erhardt Barth;Reinhard Koch;Rasmus Larsen

  • Fundamental limits of linear filters in the visual processing of two-dimensional signals.

    C. Zetzsche;E. Barth

  • A Hybrid Convolutional Variational Autoencoder for Text Generation

    Stanislau Semeniuta;Aliaksei Severyn;Erhardt Barth

  • Recurrent Dropout without Memory Loss

    Stanislau Semeniuta;Aliaksei Severyn;Erhardt Barth

  • Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning.

    Hammam A. Alshazly;Christoph Linse;Erhardt Barth;Thomas Martinetz

  • Simple Method for High-Performance Digit Recognition Based on Sparse Coding

    K. Labusch;E. Barth;T. Martinetz

  • Low-level phenomenal vision despite unilateral destruction of primary visual cortex.

    Petra Stoerig;Erhardt Barth

  • Deep convolutional neural networks as generic feature extractors

    Lars Hertel;Erhardt Barth;Thomas Kaster;Thomas Martinetz

  • The importance of intrinsically two-dimensional image features in biological vision and picture coding

    Christof Zetzsche;Erhardt Barth;Bernhard Wegmann

  • ToF-sensors: New dimensions for realism and interactivity

    A. Kolb;E. Barth;R. Koch

  • Image encoding, labeling, and reconstruction from differential geometry

    Erhardt Barth;Terry Caelli;Christoph Zetzsche

  • Analysis of Superimposed Oriented Patterns

    T. Aach;C. Mota;I. Stuke;M. Muhlich

  • Sparse Coding Neural Gas: Learning of overcomplete data representations

    Kai Labusch;Erhardt Barth;Thomas Martinetz

  • Non-parametric texture defect detection using Weibull features

    Fabian Timm;Erhardt Barth

  • Analytic solutions for multiple motions

    C. Mota;L. Stuke;E. Barth

  • Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition.

    Hammam A. Alshazly;Christoph Linse;Erhardt Barth;Thomas Martinetz

  • Remote Eye Tracking: State of the Art and Directions for Future Development

    Martin Böhme;André Meyer;Thomas Martinetz;Erhardt Barth

Frequent Co-Authors

Thomas Martinetz
Thomas Martinetz University of Lübeck
Til Aach
Til Aach RWTH Aachen University
Karl R. Gegenfurtner
Karl R. Gegenfurtner University of Giessen
Terry Caelli
Terry Caelli Deakin University
Gerhard Krieger
Gerhard Krieger German Aerospace Center
Andreas Kolb
Andreas Kolb University of Siegen
Rasmus Larsen
Rasmus Larsen Technical University of Denmark
Reinhard Koch
Reinhard Koch Kiel University
Petra Stoerig
Petra Stoerig Heinrich Heine University Düsseldorf
Remco J. Renken
Remco J. Renken University Medical Center Groningen

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