Christoph Linse

According to our database, Christoph Linse authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Rethinking generalization of classifiers in separable classes scenarios and over-parameterized regimes.

Julius Martinetz, Christoph Linse, Thomas Martinetz

Proceedings of the International Joint Conference on Neural Networks, 2024

Leaky ReLUs That Differ in Forward and Backward Pass Facilitate Activation Maximization in Deep Neural Networks.

Christoph Linse, Erhardt Barth, Thomas Martinetz

Proceedings of the International Joint Conference on Neural Networks, 2024

Enhancing Generalization in Convolutional Neural Networks Through Regularization with Edge and Line Features.

Christoph Linse, Beatrice Brückner, Thomas Martinetz

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

2023

Convolutional Neural Networks Do Work with Pre-Defined Filters.

Christoph Linse, Erhardt Barth, Thomas Martinetz

Proceedings of the International Joint Conference on Neural Networks, 2023

Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization.

Christoph Linse, Thomas Martinetz

Proceedings of the 15th International Conference on Machine Learning and Computing, 2023

2022

A walk in the black-box: 3D visualization of large neural networks in virtual reality.

Christoph Linse, Hammam A. Alshazly, Thomas Martinetz

Neural Comput. Appl., 2022

Large Neural Networks Learning from Scratch with Very Few Data and without Regularization.

Christoph Linse, Thomas Martinetz

CoRR, 2022

2021

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

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

Sensors, 2021

COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans.

Hammam A. Alshazly, Christoph Linse, Mohamed Abdalla, Erhardt Barth, Thomas Martinetz

PeerJ Comput. Sci., 2021

Towards Explainable Ear Recognition Systems Using Deep Residual Networks.

Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Sahar Ahmed Idris, Thomas Martinetz

IEEE Access, 2021

2020

Deep Convolutional Neural Networks for Unconstrained Ear Recognition.

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

IEEE Access, 2020

2019

Handcrafted versus CNN Features for Ear Recognition.

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

Symmetry, 2019

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

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

Sensors, 2019