Tobias Meisen

Tobias Meisen

Bergische Universität Wuppertal

H-index: 23

Europe-Germany

About Tobias Meisen

Tobias Meisen, With an exceptional h-index of 23 and a recent h-index of 22 (since 2020), a distinguished researcher at Bergische Universität Wuppertal, specializes in the field of Deep Learning, Deep Reinforcement Learning, Knowledge Graph.

His recent articles reflect a diverse array of research interests and contributions to the field:

End-To-End Deep Learning Material Discrimination Using Dual-Energy LINAC-CT

Survey of Deep Learning-Based Methods for FMCW Radar Odometry and Ego-Localization

Guided Exploration of Industrial Sensor Data

Deep Learning for Automated Visual Inspection in Manufacturing and Maintenance: A Survey of Open-Access Papers

It’s Not Always about Wide and Deep Models: Click-Through Rate Prediction with a Customer Behavior-Embedding Representation

Simulation Study: Data-Driven Material Decomposition in Industrial X-ray Computed Tomography

schlably: A Python Framework for Deep Reinforcement Learning Based Scheduling Experiments

Simulation-to-Reality Transfer of a Two-Stage Deep Reinforcement Learning Controller for Autonomous Load Carrier Approaching

Tobias Meisen Information

University

Position

zuvor RWTH Aachen University

Citations(all)

3396

Citations(since 2020)

2805

Cited By

1452

hIndex(all)

23

hIndex(since 2020)

22

i10Index(all)

66

i10Index(since 2020)

54

Email

University Profile Page

Bergische Universität Wuppertal

Google Scholar

View Google Scholar Profile

Tobias Meisen Skills & Research Interests

Deep Learning

Deep Reinforcement Learning

Knowledge Graph

Top articles of Tobias Meisen

Title

Journal

Author(s)

Publication Date

End-To-End Deep Learning Material Discrimination Using Dual-Energy LINAC-CT

Moritz Weiss

Nick Brierley

Mirko von Schmid

Tobias Meisen

2024

Survey of Deep Learning-Based Methods for FMCW Radar Odometry and Ego-Localization

Marvin Brune

Tobias Meisen

André Pomp

2024/3/8

Guided Exploration of Industrial Sensor Data

Computer Graphics Forum

Tristan Langer

Richard Meyes

Tobias Meisen

2024/1/29

Deep Learning for Automated Visual Inspection in Manufacturing and Maintenance: A Survey of Open-Access Papers

Nils Hütten

Miguel Alves Gomes

Florian Hölken

Karlo Andricevic

Richard Meyes

...

2024/1/22

It’s Not Always about Wide and Deep Models: Click-Through Rate Prediction with a Customer Behavior-Embedding Representation

Journal of Theoretical and Applied Electronic Commerce Research

Miguel Alves Gomes

Richard Meyes

Philipp Meisen

Tobias Meisen

2024/1/12

Simulation Study: Data-Driven Material Decomposition in Industrial X-ray Computed Tomography

NDT

Moritz Weiss

Nick Brierley

Mirko von Schmid

Tobias Meisen

2024/1/5

schlably: A Python Framework for Deep Reinforcement Learning Based Scheduling Experiments

SoftwareX

Constantin Waubert de Puiseau

Jannik Peters

Christian Dörpelkus

Hasan Tercan

Tobias Meisen

2023/5/1

Simulation-to-Reality Transfer of a Two-Stage Deep Reinforcement Learning Controller for Autonomous Load Carrier Approaching

Simon Hadwiger

Vladimir Lavrik

Li Xin Liao

Tobias Meisen

2023/4/26

An Evaluation of Link Prediction Approaches in Few-Shot Scenarios

Electronics

Rebecca Braken

Alexander Paulus

André Pomp

Tobias Meisen

2023/5/19

Chances and Challenges: Transformation from a Laser-Based to a Camera-Based Container Crane Automation System

Journal of Marine Science and Engineering

Johannes Benkert

Robert Maack

Tobias Meisen

2023/8/31

Verbesserung der Klassifikationsperformance von Deep Learning Modellen durch Reduktion der Komplexität von Seitensichtsonarbildern

Tagungsband, DAGA 2023-49. Jahrestagung für Akustik

Yannik Steiniger

Jannis Stoppe

Dieter Kraus

Tobias Meisen

2023

On the detection and classification of objects in scarce sidescan sonar image dataset with deep learning methods

7th Underwater Acoustics Conference and Exhibition, UACE 2023

Yannik Steiniger

Jannis Stoppe

Dieter Kraus

Tobias Meisen

2023

Time Series Dataset Survey for Forecasting with Deep Learning

Forecasting

Yannik Hahn

Tristan Langer

Richard Meyes

Tobias Meisen

2023/3/3

Curriculum Learning in Job Shop Scheduling using Reinforcement Learning

arXiv preprint arXiv:2305.10192

Constantin Waubert de Puiseau

Hasan Tercan

Tobias Meisen

2023/5/17

Deep representation learning and reinforcement learning for workpiece setup optimization in CNC milling

Production Engineering

Vladimir Samsonov

Enslin Chrismarie

Hans-Georg Köpken

Schirin Bär

Daniel Lütticke

...

2023/12

Using IoT Technology for the Skilled Crafts

Filipe, J., Śmiałek, M., Brodsky, A., Hammoudi, S. (eds) Enterprise Information Systems. ICEIS 2022 - Lecture Notes in Business Information Processing

André Pomp

Andreas Burgdorf

Alexander Paulus

Tobias Meisen

2023/7

A review on methods for state of health forecasting of lithium-ion batteries applicable in real-world operational conditions

Friedrich von Bülow

Tobias Meisen

2023/1/1

On The Effectiveness Of Bottleneck Information For Solving Job Shop Scheduling Problems Using Deep Reinforcement Learning

ESSN: 2701-6277

Constantin Waubert de Puiseau

Lennart Zey

Merve Demir

Hasan Tercan

Tobias Meisen

2023

Stop guessing in the dark: Identified requirements for digital product passport systems

Systems

Maike Jansen

Tobias Meisen

Christiane Plociennik

Holger Berg

André Pomp

...

2023/2/25

SPACE_DS: towards a circular economy data space

André Pomp

Maike Jansen

Holger Berg

Tobias Meisen

2023/4/30

See List of Professors in Tobias Meisen University(Bergische Universität Wuppertal)

Co-Authors

H-index: 11
Hasan Tercan

Hasan Tercan

Bergische Universität Wuppertal

H-index: 10
André Pomp

André Pomp

Bergische Universität Wuppertal

H-index: 10
Richard Meyes

Richard Meyes

Bergische Universität Wuppertal

H-index: 9
Alexander Paulus

Alexander Paulus

Bergische Universität Wuppertal

H-index: 6
Andreas Burgdorf

Andreas Burgdorf

Bergische Universität Wuppertal

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