Leonard E. van Dyck

Leonard E. van Dyck
Justus-Liebig-Universität Gießen | JLU

Master of Science

About

9
Publications
1,467
Reads
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78
Citations
Additional affiliations
October 2023 - present
Max Planck Institute for Human Cognitive and Brain Sciences
Position
  • Guest Researcher
October 2020 - February 2023
University of Salzburg
Position
  • Laboratory Manager (Method Unit EEG)
Education
October 2020 - February 2023
University of Salzburg
Field of study
  • Psychology - Cognitive Neuroscience
October 2017 - July 2020
University of Salzburg
Field of study
  • Psychology

Publications

Publications (9)
Article
Full-text available
Deep convolutional neural networks (DCNNs) and the ventral visual pathway share vast architectural and functional similarities in visual challenges such as object recognition. Recent insights have demonstrated that both hierarchical cascades can be compared in terms of both exerted behavior and underlying activation. However, these approaches ignor...
Preprint
Full-text available
Deep convolutional neural networks (DCNNs) and the ventral visual pathway share vast architectural and functional similarities in visual challenges such as object recognition. Recent insights have demonstrated that both hierarchical cascades can be compared in terms of both exerted behavior and underlying activation. However, these approaches ignor...
Preprint
Full-text available
For a considerable time, deep convolutional neural networks (DCNNs) have reached human benchmark performance in object recognition. On that account, computational neuroscience and the field of machine learning have started to attribute numerous similarities and differences to artificial and biological vision. This study aims towards a behavioral co...
Preprint
Full-text available
Deep convolutional neural networks (DCNNs) have become the state-of-the-art computational models of biological object recognition. Their remarkable success has helped vision science break new ground and recent efforts have started to transfer this achievement to research on biological face recognition. In this regard, face detection can be investig...
Article
Full-text available
Deep convolutional neural networks (DCNNs) have become the state-of-the-art computational models of biological object recognition. Their remarkable success has helped vision science break new ground, and recent efforts have started to transfer this achievement to research on biological face recognition. In this regard, face detection can be investi...
Article
Full-text available
Deep Convolutional Neural Networks (DCNNs) were originally inspired by principles of biological vision, have evolved into best current computational models of object recognition, and consequently indicate strong architectural and functional parallelism with the ventral visual pathway throughout comparisons with neuroimaging and neural time series d...
Preprint
Full-text available
Deep Convolutional Neural Networks (DCNNs) were originally inspired by principles of biological vision, have evolved into best current computational models of object recognition, and consequently indicate strong architectural and functional parallelism with the ventral visual pathway throughout comparisons with neuroimaging and neural time series d...
Article
The Internet is a common medium through which people engage in interpersonal electronic surveillance (IES) of one another. We know little empirically about what predicts IES in romantic relationships. The present study expands on factors identified in previous studies (including demographic characteristics, relational characteristics, and other psy...

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