Christoph Linse

20 papers B 3Misc 1Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	The Resurrection of the ReLU. CoRR Cosku Can Horuz, Geoffrey Kasenbacher, Saya Higuchi, Sebastian Kairat, Jendrik Stoltz, Moritz Pesl, Bernhard Alois Moser, Christoph Linse, Thomas Martinetz, Sebastian Otte
2025	—	`—`	Towards understanding convolutional neural networks through visualization and systematic simplification. Christoph Linse
2024	J	`jnl`	Convolutional Neural Networks Do Work with Pre-Defined Filters. CoRR Christoph Linse, Erhardt Barth, Thomas Martinetz
2024	—	`conf`	Enhancing Generalization in Convolutional Neural Networks Through Regularization with Edge and Line Features. ICANN (1) Christoph Linse, Beatrice Brückner, Thomas Martinetz
2024	J	`jnl`	Enhancing Generalization in Convolutional Neural Networks through Regularization with Edge and Line Features. CoRR Christoph Linse, Beatrice Brückner, Thomas Martinetz
2024	B	`conf`	Leaky ReLUs That Differ in Forward and Backward Pass Facilitate Activation Maximization in Deep Neural Networks. IJCNN Christoph Linse, Erhardt Barth, Thomas Martinetz
2024	J	`jnl`	Leaky ReLUs That Differ in Forward and Backward Pass Facilitate Activation Maximization in Deep Neural Networks. CoRR Christoph Linse, Erhardt Barth, Thomas Martinetz
2024	B	`conf`	Rethinking generalization of classifiers in separable classes scenarios and over-parameterized regimes. IJCNN Julius Martinetz, Christoph Linse, Thomas Martinetz
2024	J	`jnl`	Rethinking generalization of classifiers in separable classes scenarios and over-parameterized regimes. CoRR Julius Martinetz, Christoph Linse, Thomas Martinetz
2023	B	`conf`	Convolutional Neural Networks Do Work with Pre-Defined Filters. IJCNN Christoph Linse, Erhardt Barth, Thomas Martinetz
2023	Misc	`conf`	Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization. ICMLC Christoph Linse, Thomas Martinetz
2022	J	`jnl`	A walk in the black-box: 3D visualization of large neural networks in virtual reality. Neural Comput. Appl. Christoph Linse, Hammam A. Alshazly, Thomas Martinetz
2022	J	`jnl`	Large Neural Networks Learning from Scratch with Very Few Data and without Regularization. CoRR Christoph Linse, Thomas Martinetz
2021	J	`jnl`	COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans. PeerJ Comput. Sci. Hammam A. Alshazly, Christoph Linse, Mohamed Abdalla, Erhardt Barth, Thomas Martinetz
2021	J	`jnl`	Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning. Sensors Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
2021	J	`jnl`	Towards Explainable Ear Recognition Systems Using Deep Residual Networks. IEEE Access Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Sahar Ahmed Idris, Thomas Martinetz
2020	J	`jnl`	Deep Convolutional Neural Networks for Unconstrained Ear Recognition. IEEE Access Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
2020	J	`jnl`	Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning. CoRR Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
2019	J	`jnl`	Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition. Sensors Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
2019	J	`jnl`	Handcrafted versus CNN Features for Ear Recognition. Symmetry Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz