Universität Lübeck

research

∙ 02/28/2022

"If you could see me through my eyes": Predicting Pedestrian Perception

Pedestrians are particularly vulnerable road users in urban traffic. Wit...

Julian Petzold, et al. ∙

research

∙ 08/01/2021

Applications of Artificial Neural Networks in Microorganism Image Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to Popular Convolutional Neural Netwo

Microorganisms are widely distributed in the human daily living environm...

Jinghua Zhang, et al. ∙

research

∙ 07/25/2019

Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks

Nonlinear image registration continues to be a fundamentally important t...

Mattias P. Heinrich, et al. ∙

research

∙ 12/08/2021

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

To date few studies have comprehensively compared medical image registra...

Alessa Hering, et al. ∙

research

∙ 07/11/2019

Robust GPU-based Virtual Reality Simulation of Radio Frequency Ablations for Various Needle Geometries and Locations

Purpose: Radio-frequency ablations play an important role in the therapy...

Niclas Kath, et al. ∙

research

∙ 03/16/2016

Recurrent Dropout without Memory Loss

This paper presents a novel approach to recurrent neural network (RNN) r...

Stanislau Semeniuta, et al. ∙

research

∙ 01/06/2022

Bio-inspired Min-Nets Improve the Performance and Robustness of Deep Networks

Min-Nets are inspired by end-stopped cortical cells with units that outp...

Philipp Grüning, et al. ∙

research

∙ 09/17/2019

Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients

Deformable registration continues to be one of the key challenges in med...

Lasse Hansen, et al. ∙

research

∙ 05/26/2020

Learning to map between ferns with differentiable binary embedding networks

Current deep learning methods are based on the repeated, expensive appli...

Max Blendowski, et al. ∙

research

∙ 05/27/2020

Tackling the Problem of Large Deformations in Deep Learning Based Medical Image Registration Using Displacement Embeddings

Though, deep learning based medical image registration is currently star...

Lasse Hansen, et al. ∙

research

∙ 05/28/2020

Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Move's discrepancies

Multimodal image registration is a very challenging problem for deep lea...

Mattias P. Heinrich, et al. ∙

research

∙ 07/06/2020

Solving Packing Problems with Few Small Items Using Rainbow Matchings

An important area of combinatorial optimization is the study of packing ...

Max Bannach, et al. ∙

research

∙ 04/20/2021

Robust Online Algorithms for Dynamic Choosing Problems

Semi-online algorithms that are allowed to perform a bounded amount of r...

Sebastian Berndt, et al. ∙

research

∙ 08/18/2021

Automatic Centralized Control of Underactuated Large-scale Multi-robot Systems using a Generalized Coordinate Transformation

Controlling large-scale particle or robot systems is challenging because...

Babak Salamat, et al. ∙

research

∙ 11/24/2021

On the convergence of Broyden's method and some accelerated schemes for singular problems

We consider Broyden's method and some accelerated schemes for nonlinear ...

Florian Mannel, et al. ∙

research

∙ 12/06/2021

Fast 3D registration with accurate optimisation and little learning for Learn2Reg 2021

Current approaches for deformable medical image registration often strug...

Hanna Siebert, et al. ∙

research

∙ 12/14/2021

Cross-modal Music Emotion Recognition Using Composite Loss-based Embeddings

Most music emotion recognition approaches use one-way classification or ...

Naoki Takashima, et al. ∙

research

∙ 11/22/2022

Anatomy-guided domain adaptation for 3D in-bed human pose estimation

3D human pose estimation is a key component of clinical monitoring syste...

Alexander Bigalke, et al. ∙

research

∙ 01/10/2022

Comparison of Representation Learning Techniques for Tracking in time resolved 3D Ultrasound

3D ultrasound (3DUS) becomes more interesting for target tracking in rad...

Daniel Wulff, et al. ∙

research

∙ 01/18/2022

Speed-vs-Accuracy Tradeoff in Collective Estimation: An Adaptive Exploration-Exploitation Case

The tradeoff between accuracy and speed is considered fundamental to ind...

Mohsen Raoufi, et al. ∙

research

∙ 02/23/2022

Using Deep Reinforcement Learning with Automatic Curriculum earning for Mapless Navigation in Intralogistics

We propose a deep reinforcement learning approach for solving a mapless ...

Honghu Xue, et al. ∙

research

∙ 05/18/2022

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

Recent findings have shown that Neural Networks generalize also in over-...

Christoph Linse, et al. ∙

research

∙ 05/20/2022

Automatic Generation of Synthetic Colonoscopy Videos for Domain Randomization

An increasing number of colonoscopic guidance and assistance systems rel...

Abhishek Dinkar Jagtap, et al. ∙

research

∙ 07/01/2022

Adapting the Mean Teacher for keypoint-based lung registration under geometric domain shifts

Recent deep learning-based methods for medical image registration achiev...

Alexander Bigalke, et al. ∙

research

∙ 08/08/2022

A review on longitudinal data analysis with random forest in precision medicine

Precision medicine provides customized treatments to patients based on t...

Jianchang Hu, et al. ∙

research

∙ 08/15/2022

Learn2Trust: A video and streamlit-based educational programme for AI-based medical image analysis targeted towards medical students

In order to be able to use artificial intelligence (AI) in medicine with...

Hanna Siebert, et al. ∙

research

∙ 08/24/2022

Weakly Supervised Airway Orifice Segmentation in Video Bronchoscopy

Video bronchoscopy is routinely conducted for biopsies of lung tissue su...

Ron Keuth, et al. ∙

research

∙ 08/31/2022

Microwalk-CI: Practical Side-Channel Analysis for JavaScript Applications

Secret-dependent timing behavior in cryptographic implementations has re...

Jan Wichelmann, et al. ∙

research

∙ 11/07/2022

Highly over-parameterized classifiers generalize since bad solutions are rare

We study the generalization of over-parameterized classifiers where Empi...

Julius Martinetz, et al. ∙

research

∙ 12/05/2017

Population-based Respiratory 4D Motion Atlas Construction and its Application for VR Simulations of Liver Punctures

Virtual reality (VR) training simulators of liver needle insertion in th...

Andre Mastmeyer, et al. ∙

research

∙ 08/03/2018

DeepCloak: Adversarial Crafting As a Defensive Measure to Cloak Processes

Over the past decade, side-channels have proven to be significant and pr...

Mehmet Sinan Inci, et al. ∙

research

∙ 08/03/2017

Image reconstruction with imperfect forward models and applications in deblurring

We present and analyse an approach to image reconstruction problems with...

Yury Korolev, et al. ∙

research

∙ 07/26/2017

Interpatient Respiratory Motion Model Transfer for Virtual Reality Simulations of Liver Punctures

Current virtual reality (VR) training simulators of liver punctures ofte...

Andre Mastmeyer, et al. ∙

research

∙ 08/02/2015

Learning from Pairwise Marginal Independencies

We consider graphs that represent pairwise marginal independencies among...

Johannes Textor, et al. ∙

research

∙ 05/11/2016

Random forests for survival analysis using maximally selected rank statistics

The most popular approach for analyzing survival data is the Cox regress...

Marvin N. Wright, et al. ∙

research

∙ 02/08/2017

A Hybrid Convolutional Variational Autoencoder for Text Generation

In this paper we explore the effect of architectural choices on learning...

Stanislau Semeniuta, et al. ∙

research

∙ 01/29/2018

TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions

Deep convolutional neural networks (DCNN) are currently ubiquitous in me...

Mattias P. Heinrich, et al. ∙

research

∙ 02/22/2018

Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks

Autonomous robots need to interact with unknown, unstructured and changi...

Daniel Tanneberg, et al. ∙

research

∙ 04/12/2018

On the Application of ISO 26262 in Control Design for Automated Vehicles

Research on automated vehicles has experienced an explosive growth over ...

Georg Schildbach, et al. ∙

research

∙ 04/18/2018

A Robot to Shape your Natural Plant: The Machine Learning Approach to Model and Control Bio-Hybrid Systems

Bio-hybrid systems---close couplings of natural organisms with technolog...

Mostafa Wahby, et al. ∙

research

∙ 06/13/2018

On Accurate Evaluation of GANs for Language Generation

Generative Adversarial Networks (GANs) are a promising approach to langu...

Stanislau Semeniuta, et al. ∙

research

∙ 06/26/2018

Practical Access to Dynamic Programming on Tree Decompositions

Parameterized complexity theory has lead to a wide range of algorithmic ...

Max Bannach, et al. ∙

research

∙ 07/02/2018

Fusing First-order Knowledge Compilation and the Lifted Junction Tree Algorithm

Standard approaches for inference in probabilistic formalisms with first...

Tanya Braun, et al. ∙

research

∙ 07/10/2018

Computing Kernels in Parallel: Lower and Upper Bounds

Parallel fixed-parameter tractability studies how parameterized problems...

Max Bannach, et al. ∙

research

∙ 08/13/2019

Loop Closure Detection in Closed Environments

Low cost robots, such as vacuum cleaners or lawn mowers employ simplisti...

Nils Rottmann, et al. ∙

research

∙ 08/16/2018

MicroWalk: A Framework for Finding Side Channels in Binaries

Microarchitectural side channels expose unprotected software to informat...

Jan Wichelmann, et al. ∙

research

∙ 09/14/2018

Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds

Graph convolutional networks are a new promising learning approach to de...

Lasse Hansen, et al. ∙

research

∙ 11/27/2018

Undermining User Privacy on Mobile Devices Using AI

Over the past years, literature has shown that attacks exploiting the mi...

Berk Gulmezoglu, et al. ∙

research

∙ 01/10/2019

On the Descriptive Complexity of Color Coding

Color coding is an algorithmic technique used in parameterized complexit...

Max Bannach, et al. ∙

research

∙ 01/25/2019

Empowering individual trait prediction using interactions

One component of precision medicine is to construct prediction models wi...

Damian Gola, et al. ∙

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