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Ralf Mikut
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2020 – today
- 2024
- [j74]Simon Baeuerle, Marius Gebhardt, Jonas Barth, Ralf Mikut, Andreas Steimer:
Rapid Flow Behavior Modeling of Thermal Interface Materials Using Deep Neural Networks. IEEE Access 12: 17782-17792 (2024) - [j73]Kaleb Phipps, Benedikt Heidrich, Marian Turowski, Moritz Wittig, Ralf Mikut, Veit Hagenmeyer:
Generating probabilistic forecasts from arbitrary point forecasts using a conditional invertible neural network. Appl. Intell. 54(8): 6354-6382 (2024) - [j72]Miguel Molina-Moreno, Iván González-Díaz, Ralf Mikut, Fernando Díaz-de-María:
A self-supervised embedding of cell migration features for behavior discovery over cell populations. Comput. Methods Programs Biomed. 255: 108337 (2024) - [j71]Nicole Merkle, Ralf Mikut:
Context-aware composition of agent policies by Markov decision process entity embeddings and agent ensembles. Semantic Web 15(4): 1443-1471 (2024) - [j70]Johannes Seiffarth, Tim Scherr, Bastian Wollenhaupt, Oliver Neumann, Hanno Scharr, Dietrich Kohlheyer, Ralf Mikut, Katharina Nöh:
ObiWan-Microbi: OMERO-based integrated workflow for annotating microbes in the cloud. SoftwareX 26: 101638 (2024) - [c46]Rafael Poppenborg, Kaleb Phipps, Maximilian Beichter, Kevin Förderer, Ralf Mikut, Veit Hagenmeyer:
Dynamic Phenotype Mapping in Evolutionary Algorithms for Energy Hub Scheduling. EI.A (2) 2024: 205-223 - [c45]Stefan Meisenbacher, Johannes Galenzowski, Kevin Förderer, Wolfgang Süß, Simon Waczowicz, Ralf Mikut, Veit Hagenmeyer:
Automation Level Taxonomy for Time Series Forecasting Services: Guideline for Real-World Smart Grid Applications. EI.A (1) 2024: 277-297 - [i45]David Wölfle, Kevin Förderer, Tobias Riedel, Lukas Landwich, Ralf Mikut, Veit Hagenmeyer, Hartmut Schmeck:
Open Energy Services - Forecasting and Optimization as a Service for Energy Management Applications at Scale. CoRR abs/2402.15230 (2024) - [i44]Alina Pleli, Simon Baeuerle, Michel Janus, Jonas Barth, Ralf Mikut, Hendrik P. A. Lensch:
Iterative Cluster Harvesting for Wafer Map Defect Patterns. CoRR abs/2404.15436 (2024) - [i43]Simon Baeuerle, Andreas Steimer, Ralf Mikut:
Coverage Path Planning for Thermal Interface Materials. CoRR abs/2405.13512 (2024) - [i42]Manuel Treutlein, Marc Schmidt, Roman Hahn, Matthias Hertel, Benedikt Heidrich, Ralf Mikut, Veit Hagenmeyer:
Generating peak-aware pseudo-measurements for low-voltage feeders using metadata of distribution system operators. CoRR abs/2409.19713 (2024) - 2023
- [j69]Benedikt Heidrich, Marian Turowski, Kaleb Phipps, Kai Schmieder, Wolfgang Süß, Ralf Mikut, Veit Hagenmeyer:
Controlling non-stationarity and periodicities in time series generation using conditional invertible neural networks. Appl. Intell. 53(8): 8826-8843 (2023) - [j68]Ralf Mikut, Andreas Kroll, Horst Schulte:
Selected contributions from the Workshop "Computational Intelligence". Autom. 71(10): 817-819 (2023) - [j67]Yanke Wang, Christian Pylatiuk, Ralf Mikut, Ravindra Peravali, Markus Reischl:
A fully automated touch-response behavior inspection pipeline on zebrafish larvae. Autom. 71(10): 845-852 (2023) - [j66]Patricia M. Dold, Fabian Bleier, Meiko Boley, Ralf Mikut:
Two-stage quality monitoring of a laser welding process using machine learning: An approach for fast yet precise quality monitoring. Autom. 71(10): 878-890 (2023) - [j65]Matthias Hertel, Maximilian Beichter, Benedikt Heidrich, Oliver Neumann, Benjamin Schäfer, Ralf Mikut, Veit Hagenmeyer:
Transformer training strategies for forecasting multiple load time series. Energy Inform. 6(1): 20 (2023) - [j64]Oliver Neumann, Marian Turowski, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig:
Using weather data in energy time series forecasting: the benefit of input data transformations. Energy Inform. 6(1): 44 (2023) - [j63]Kaleb Phipps, Karl Schwenk, Benjamin Briegel, Ralf Mikut, Veit Hagenmeyer:
Customized Uncertainty Quantification of Parking Duration Predictions for EV Smart Charging. IEEE Internet Things J. 10(23): 20649-20661 (2023) - [c44]Dorina Werling, Maximilian Beichter, Benedikt Heidrich, Kaleb Phipps, Ralf Mikut, Veit Hagenmeyer:
The Impact of Forecast Characteristics on the Forecast Value for the Dispatchable Feeder. e-Energy (Companion) 2023: 59-71 - [c43]Kaleb Phipps, Stefan Meisenbacher, Benedikt Heidrich, Marian Turowski, Ralf Mikut, Veit Hagenmeyer:
Loss-Customised Probabilistic Energy Time Series Forecasts Using Automated Hyperparameter Optimisation. e-Energy 2023: 271-286 - [c42]Stefan Meisenbacher, Benedikt Heidrich, Tim Martin, Ralf Mikut, Veit Hagenmeyer:
AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models. e-Energy 2023: 386-414 - [c41]Marian Turowski, Oliver Neumann, Lisa Mannsperger, Kristof Kraus, Kira Layer, Ralf Mikut, Veit Hagenmeyer:
Managing Anomalies in Energy Time Series for Automated Forecasting. EI.A 2023: 3-29 - [c40]Dorina Werling, Maximilian Beichter, Benedikt Heidrich, Kaleb Phipps, Ralf Mikut, Veit Hagenmeyer:
Automating Value-Oriented Forecast Model Selection by Meta-learning: Application on a Dispatchable Feeder. EI.A 2023: 95-116 - [c39]Rafael Poppenborg, Kaleb Phipps, Hatem Khalloof, Kevin Förderer, Ralf Mikut, Veit Hagenmeyer:
Dynamic Chromosome Interpretation in Evolutionary Algorithms for Distributed Energy Resources Scheduling. GECCO Companion 2023: 755-758 - [c38]Miguel Molina-Moreno, Marcel P. Schilling, Markus Reischl, Ralf Mikut:
Automated Style-Aware Selection of Annotated Pre-Training Databases in Biomedical Imaging. ISBI 2023: 1-5 - [c37]Johannes Galenzowski, Simon Waczowicz, Stefan Meisenbacher, Ralf Mikut, Veit Hagenmeyer:
A Real-World District Community Platform as a Cyber-Physical-Social Infrastructure Systems in the Energy Domain. BuildSys@SenSys 2023: 434-441 - [i41]Kaleb Phipps, Benedikt Heidrich, Marian Turowski, Moritz Wittig, Ralf Mikut, Veit Hagenmeyer:
Creating Probabilistic Forecasts from Arbitrary Deterministic Forecasts using Conditional Invertible Neural Networks. CoRR abs/2302.01800 (2023) - [i40]Benedikt Heidrich, Kaleb Phipps, Oliver Neumann, Marian Turowski, Ralf Mikut, Veit Hagenmeyer:
ProbPNN: Enhancing Deep Probabilistic Forecasting with Statistical Information. CoRR abs/2302.02597 (2023) - [i39]Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Martin Weigert, Uwe Schmidt, Wenhua Zhang, Jun Zhang, Sen Yang, Jinxi Xiang, Xiyue Wang, Josef Lorenz Rumberger, Elias Baumann, Peter Hirsch, Lihao Liu, Chenyang Hong, Angelica I. Avilés-Rivero, Ayushi Jain, Heeyoung Ahn, Yiyu Hong, Hussam Azzuni, Min Xu, Mohammad Yaqub, Marie-Claire Blache, Benoît Piégu, Bertrand Vernay, Tim Scherr, Moritz Böhland, Katharina Löffler, Jiachen Li, Weiqin Ying, Chixin Wang, Dagmar Kainmueller, Carola-Bibiane Schönlieb, Shuolin Liu, Dhairya Talsania, Yughender Meda, Prakash Mishra, Muhammad Ridzuan, Oliver Neumann, Marcel P. Schilling, Markus Reischl, Ralf Mikut, Banban Huang, Hsiang-Chin Chien, Ching-Ping Wang, Chia-Yen Lee, Hong-Kun Lin, Zaiyi Liu, Xipeng Pan, Chu Han, Jijun Cheng, Muhammad Dawood, Srijay Deshpande, Raja Muhammad Saad Bashir, Adam Shephard, Pedro Costa, João D. Nunes, Aurélio Campilho, Jaime S. Cardoso, Hrishikesh P. S, Densen Puthussery, Devika R. G, Jiji C V, Ye Zhang, Zijie Fang, Zhifan Lin, Yongbing Zhang, Chunhui Lin, Liukun Zhang, Lijian Mao, Min Wu, Thi Tuong Vi Vo, Soo-Hyung Kim, Taebum Lee, Satoshi Kondo, Satoshi Kasai, Pranay Dumbhare, Vedant Phuse, Yash Dubey, Ankush Jamthikar, Trinh Thi Le Vuong, Jin Tae Kwak, Dorsa Ziaei, Hyun Jung, Tianyi Miao, David R. J. Snead, Shan-E-Ahmed Raza, Fayyaz Minhas, Nasir M. Rajpoot:
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting. CoRR abs/2303.06274 (2023) - [i38]Matthias Hertel, Maximilian Beichter, Benedikt Heidrich, Oliver Neumann, Benjamin Schäfer, Ralf Mikut, Veit Hagenmeyer:
Transformer Training Strategies for Forecasting Multiple Load Time Series. CoRR abs/2306.10891 (2023) - [i37]Nicole Merkle, Ralf Mikut:
Context-Aware Composition of Agent Policies by Markov Decision Process Entity Embeddings and Agent Ensembles. CoRR abs/2308.14521 (2023) - [i36]Angelo Jovin Yamachui Sitcheu, Nils Friederich, Simon Baeuerle, Oliver Neumann, Markus Reischl, Ralf Mikut:
MLOps for Scarce Image Data: A Use Case in Microscopic Image Analysis. CoRR abs/2309.15521 (2023) - [i35]Nils Friederich, Angelo Jovin Yamachui Sitcheu, Oliver Neumann, Süheyla Eroglu-Kayikçi, Roshan Prizak, Lennart Hilbert, Ralf Mikut:
AI-based automated active learning for discovery of hidden dynamic processes: A use case in light microscopy. CoRR abs/2310.04461 (2023) - 2022
- [j62]Marcel P. Schilling, Tim Scherr, Friedrich R. Münke, Oliver Neumann, Mark Schutera, Ralf Mikut, Markus Reischl:
Automated Annotator Variability Inspection for Biomedical Image Segmentation. IEEE Access 10: 2753-2765 (2022) - [j61]Katharina Löffler, Ralf Mikut:
EmbedTrack - Simultaneous Cell Segmentation and Tracking Through Learning Offsets and Clustering Bandwidths. IEEE Access 10: 77147-77157 (2022) - [j60]Peter Bretschneider, Ralf Mikut, Veit Hagenmeyer:
Hardware-in-the-loop platforms for the automation and control of future energy systems. Autom. 70(12): 1031-1033 (2022) - [j59]Friedrich Wiegel, Jan Wachter, Michael Kyesswa, Ralf Mikut, Simon Waczowicz, Veit Hagenmeyer:
Smart Energy System Control Laboratory - a fully-automated and user-oriented research infrastructure for controlling and operating smart energy systems. Autom. 70(12): 1116-1133 (2022) - [j58]Maximilian Beichter, Kaleb Phipps, Martha Maria Frysztacki, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig:
Net load forecasting using different aggregation levels. Energy Inform. 5 (2022) - [j57]Benedikt Heidrich, Lisa Mannsperger, Marian Turowski, Kaleb Phipps, Benjamin Schäfer, Ralf Mikut, Veit Hagenmeyer:
Boost short-term load forecasts with synthetic data from transferred latent space information. Energy Inform. 5 (2022) - [j56]Baifan Zhou, Tim Pychynski, Markus Reischl, Evgeny Kharlamov, Ralf Mikut:
Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding. J. Intell. Manuf. 33(4): 1139-1163 (2022) - [j55]Yanke Wang, Naveen Krishna Kanagaraj, Christian Pylatiuk, Ralf Mikut, Ravindra Peravali, Markus Reischl:
High-Throughput Data Acquisition Platform for Multi-Larvae Touch-Response Behavior Screening of Zebrafish. IEEE Robotics Autom. Lett. 7(2): 858-865 (2022) - [j54]Yanke Wang, Daniel Marcato, Vani Tirumalasetty, Naveen Krishna Kanagaraj, Christian Pylatiuk, Ralf Mikut, Ravindra Peravali, Markus Reischl:
An Automated Experimentation System for the Touch-Response Quantification of Zebrafish Larvae. IEEE Trans Autom. Sci. Eng. 19(4): 3007-3019 (2022) - [j53]Stefan Meisenbacher, Marian Turowski, Kaleb Phipps, Martin Rätz, Dirk Müller, Veit Hagenmeyer, Ralf Mikut:
Review of automated time series forecasting pipelines. WIREs Data Mining Knowl. Discov. 12(6) (2022) - [c36]Marian Turowski, Benedikt Heidrich, Kaleb Phipps, Kai Schmieder, Oliver Neumann, Ralf Mikut, Veit Hagenmeyer:
Enhancing anomaly detection methods for energy time series using latent space data representations. e-Energy 2022: 208-227 - [c35]Benedikt Heidrich, Nicole Ludwig, Marian Turowski, Ralf Mikut, Veit Hagenmeyer:
Adaptively coping with concept drifts in energy time series forecasting using profiles. e-Energy 2022: 459-470 - [c34]Marian Turowski, Moritz Weber, Oliver Neumann, Benedikt Heidrich, Kaleb Phipps, Hüseyin Kemâl Çakmak, Ralf Mikut, Veit Hagenmeyer:
Modeling and generating synthetic anomalies for energy and power time series. e-Energy 2022: 471-484 - [c33]David Bethge, Philipp Hallgarten, Ozan Özdenizci, Ralf Mikut, Albrecht Schmidt, Tobias Grosse-Puppendahl:
Exploiting Multiple EEG Data Domains with Adversarial Learning. EMBC 2022: 3154-3158 - [c32]David Bethge, Philipp Hallgarten, Tobias Grosse-Puppendahl, Mohamed Kari, Ralf Mikut, Albrecht Schmidt, Ozan Özdenizci:
Domain-Invariant Representation Learning from EEG with Private Encoders. ICASSP 2022: 1236-1240 - [c31]Moritz Frahm, Felix Langner, Philipp Zwickel, Jörg Matthes, Ralf Mikut, Veit Hagenmeyer:
How to Derive and Implement a Minimalistic RC Model from Thermodynamics for the Control of Thermal Parameters for Assuring Thermal Comfort in Buildings. OSMSES 2022: 1-6 - [c30]Moritz Frahm, Stefan Meisenbacher, Elena Klumpp, Ralf Mikut, Jörg Matthes, Veit Hagenmeyer:
Multi-zone grey-box thermal building identification with real occupants. BuildSys@SenSys 2022: 484-487 - [i34]David Bethge, Philipp Hallgarten, Tobias Grosse-Puppendahl, Mohamed Kari, Ralf Mikut, Albrecht Schmidt, Ozan Özdenizci:
Domain-Invariant Representation Learning from EEG with Private Encoders. CoRR abs/2201.11613 (2022) - [i33]Stefan Meisenbacher, Marian Turowski, Kaleb Phipps, Martin Rätz, Dirk Müller, Veit Hagenmeyer, Ralf Mikut:
Review of automated time series forecasting pipelines. CoRR abs/2202.01712 (2022) - [i32]Moritz Böhland, Oliver Neumann, Marcel P. Schilling, Markus Reischl, Ralf Mikut, Katharina Löffler, Tim Scherr:
ciscNet - A Single-Branch Cell Instance Segmentation and Classification Network. CoRR abs/2202.13960 (2022) - [i31]David Bethge, Philipp Hallgarten, Ozan Özdenizci, Ralf Mikut, Albrecht Schmidt, Tobias Grosse-Puppendahl:
Exploiting Multiple EEG Data Domains with Adversarial Learning. CoRR abs/2204.07777 (2022) - [i30]Katharina Löffler, Ralf Mikut:
EmbedTrack - Simultaneous Cell Segmentation and Tracking Through Learning Offsets and Clustering Bandwidths. CoRR abs/2204.10713 (2022) - [i29]Simon Baeuerle, Marius Gebhardt, Jonas Barth, Andreas Steimer, Ralf Mikut:
Rapid Flow Behavior Modeling of Thermal Interface Materials Using Deep Neural Networks. CoRR abs/2208.04045 (2022) - [i28]Thorbjørn Lund Onsaker, Heidi S. Nygård, Damià Gomila, Pere Colet, Ralf Mikut, Richard Jumar, Heiko Maaß, Uwe G. Kühnapfel, Veit Hagenmeyer, Dirk Witthaut, Benjamin Schäfer:
Predicting the power grid frequency of European islands. CoRR abs/2209.15414 (2022) - [i27]Oliver Neumann, Marcel P. Schilling, Markus Reischl, Ralf Mikut:
EasyMLServe: Easy Deployment of REST Machine Learning Services. CoRR abs/2211.14417 (2022) - [i26]Stefan Meisenbacher, Benedikt Heidrich, Tim Martin, Ralf Mikut, Veit Hagenmeyer:
AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models. CoRR abs/2212.06797 (2022) - 2021
- [j52]Ralf Mikut, Andreas Kroll, Horst Schulte:
Ausgewählte Beiträge aus dem GMA-Fachausschuss 5.14 "Computational Intelligence". Autom. 69(10): 817-819 (2021) - [j51]Simon Bäuerle, Moritz Böhland, Jonas Barth, Markus Reischl, Andreas Steimer, Ralf Mikut:
CAD-to-real: enabling deep neural networks for 3D pose estimation of electronic control units. Autom. 69(10): 880-891 (2021) - [j50]Friedrich R. Münke, Marcel P. Schilling, Ralf Mikut, Markus Reischl:
Evaluierung von Merkmalen zur Abbildung von Veränderungen in ungeordneten Bilddaten. Autom. 69(10): 892-902 (2021) - [j49]Mark Schutera, Frank M. Hafner, Jochen Abhau, Veit Hagenmeyer, Ralf Mikut, Markus Reischl:
Cuepervision: self-supervised learning for continuous domain adaptation without catastrophic forgetting. Image Vis. Comput. 106: 104079 (2021) - [j48]Mark Schutera, Mostafa Hussein, Jochen Abhau, Ralf Mikut, Markus Reischl:
Night-to-Day: Online Image-to-Image Translation for Object Detection Within Autonomous Driving by Night. IEEE Trans. Intell. Veh. 6(3): 480-489 (2021) - [j47]Karl Schwenk, Stefan Meisenbacher, Benjamin Briegel, Tim Harr, Veit Hagenmeyer, Ralf Mikut:
Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles. IEEE Trans. Smart Grid 12(6): 5135-5145 (2021) - [j46]Moritz Weber, Marian Turowski, Hüseyin Kemâl Çakmak, Ralf Mikut, Uwe G. Kühnapfel, Veit Hagenmeyer:
Data-Driven Copy-Paste Imputation for Energy Time Series. IEEE Trans. Smart Grid 12(6): 5409-5419 (2021) - [j45]Baifan Zhou, Yulia Svetashova, Andre Gusmao, Ahmet Soylu, Gong Cheng, Ralf Mikut, Arild Waaler, Evgeny Kharlamov:
SemML: Facilitating development of ML models for condition monitoring with semantics. J. Web Semant. 71: 100664 (2021) - [c29]Stefan Meisenbacher, Karl Schwenk, Johannes Galenzowski, Simon Waczowicz, Ralf Mikut, Veit Hagenmeyer:
Smart Charging of Electric Vehicles with Cloud-based Optimization and a Lightweight User Interface: A Real-World Application in the Energy Lab 2.0: Poster. e-Energy 2021: 284-285 - [c28]Karl Schwenk, Kaleb Phipps, Benjamin Briegel, Veit Hagenmeyer, Ralf Mikut:
A Benchmark for Parking Duration Prediction of Electric Vehicles for Smart Charging Applications. SSCI 2021: 1-8 - [i25]Moritz Weber, Marian Turowski, Hüseyin Kemâl Çakmak, Ralf Mikut, Uwe G. Kühnapfel, Veit Hagenmeyer:
Data-Driven Copy-Paste Imputation for Energy Time Series. CoRR abs/2101.01423 (2021) - [i24]Vinayak Sharma, Jorge Ángel González Ordiano, Ralf Mikut, Umit Cali:
Probabilistic Solar Power Forecasting: Long Short-Term Memory Network vs Simpler Approaches. CoRR abs/2101.08236 (2021) - [i23]Benedikt Heidrich, Andreas Bartschat, Marian Turowski, Oliver Neumann, Kaleb Phipps, Stefan Meisenbacher, Kai Schmieder, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer:
pyWATTS: Python Workflow Automation Tool for Time Series. CoRR abs/2106.10157 (2021) - [i22]Stefan Meisenbacher, Janik Pinter, Tim Martin, Veit Hagenmeyer, Ralf Mikut:
Concepts for Automated Machine Learning in Smart Grid Applications. CoRR abs/2110.13585 (2021) - [i21]Oliver Neumann, Nicole Ludwig, Marian Turowski, Benedikt Heidrich, Veit Hagenmeyer, Ralf Mikut:
Smart Data Representations: Impact on the Accuracy of Deep Neural Networks. CoRR abs/2111.09128 (2021) - [i20]Marcel P. Schilling, Luca Rettenberger, Friedrich R. Münke, Haijun Cui, Anna A. Popova, Pavel A. Levkin, Ralf Mikut, Markus Reischl:
Label Assistant: A Workflow for Assisted Data Annotation in Image Segmentation Tasks. CoRR abs/2111.13970 (2021) - 2020
- [j44]Ralf Mikut:
Maschinelles Lernen und Künstliche Intelligenz - Eine Revolution in der Automatisierungstechnik oder nur ein Hype? Autom. 68(5): 295-300 (2020) - [j43]Tim Scherr, Karolin Streule, Andreas Bartschat, Moritz Böhland, Johannes Stegmaier, Markus Reischl, Véronique Orian-Rousseau, Ralf Mikut:
BeadNet: deep learning-based bead detection and counting in low-resolution microscopy images. Bioinform. 36(17): 4668-4670 (2020) - [c27]Baifan Zhou, Yulia Svetashova, Seongsu Byeon, Tim Pychynski, Ralf Mikut, Evgeny Kharlamov:
Predicting Quality of Automated Welding with Machine Learning and Semantics: A Bosch Case Study. CIKM 2020: 2933-2940 - [c26]Benedikt Heidrich, Marian Turowski, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer:
Forecasting energy time series with profile neural networks. e-Energy 2020: 220-230 - [c25]Sourabh Bhide, Ralf Mikut, Maria Leptin, Johannes Stegmaier:
Semi-Automatic Generation Of Tight Binary Masks And Non-Convex Isosurfaces For Quantitative Analysis Of 3d Biological Samples. ICIP 2020: 2820-2824 - [c24]Long Wang, Marian Turowski, Meng Zhang, Till Riedel, Michael Beigl, Ralf Mikut, Veit Hagenmeyer:
Point and contextual anomaly detection in building load profiles of a university campus. ISGT-Europe 2020: 11-15 - [c23]Yulia Svetashova, Baifan Zhou, Tim Pychynski, Stefan Schmidt, York Sure-Vetter, Ralf Mikut, Evgeny Kharlamov:
Ontology-Enhanced Machine Learning: A Bosch Use Case of Welding Quality Monitoring. ISWC (2) 2020: 531-550 - [i19]Sourabh Bhide, Ralf Mikut, Maria Leptin, Johannes Stegmaier:
Semi-Automatic Generation of Tight Binary Masks and Non-Convex Isosurfaces for Quantitative Analysis of 3D Biological Samples. CoRR abs/2001.11469 (2020) - [i18]Tim Scherr, Katharina Löffler, Moritz Böhland, Ralf Mikut:
Cell Segmentation and Tracking using Distance Transform Predictions and Movement Estimation with Graph-Based Matching. CoRR abs/2004.01486 (2020) - [i17]Ivan Kovynyov, Axel Buerck, Ralf Mikut:
Design of Transformation Initiatives Implementing Organisational Agility - An Empirical Study. CoRR abs/2006.00048 (2020) - [i16]Simon Baeuerle, Jonas Barth, Elton Renato Tavares de Menezes, Andreas Steimer, Ralf Mikut:
CAD2Real: Deep learning with domain randomization of CAD data for 3D pose estimation of electronic control unit housings. CoRR abs/2009.12312 (2020)
2010 – 2019
- 2019
- [j42]Mark Schutera, Stefan Elser, Jochen Abhau, Ralf Mikut, Markus Reischl:
Strategies for supplementing recurrent neural network training for spatio-temporal prediction. Autom. 67(7): 545-556 (2019) - [j41]Ralf Mikut, Andreas Kroll, Frank Hoffmann:
Ausgewählte Beiträge aus dem GMA-Fachausschuss 5.14 "Computational Intelligence". Autom. 67(10): 817-819 (2019) - [j40]Moritz Böhland, Wolfgang Doneit, Lutz Gröll, Ralf Mikut, Markus Reischl:
Automated design process for hybrid regression modeling with a one-class SVM. Autom. 67(10): 843-852 (2019) - [j39]Andreas Bartschat, Stephan Allgeier, Tim Scherr, Johannes Stegmaier, Sebastian Bohn, Klaus-Martin Reichert, Arjan Kuijper, Markus Reischl, Oliver Stachs, Bernd Köhler, Ralf Mikut:
Fuzzy tissue detection for real-time focal control in corneal confocal microscopy. Autom. 67(10): 879-888 (2019) - [j38]Markus Reischl, Mazin Jouda, Neil MacKinnon, Erwin Fuhrer, Natalia Bakhtina, Andreas Bartschat, Ralf Mikut, Jan G. Korvink:
Motion prediction enables simulated MR-imaging of freely moving model organisms. PLoS Comput. Biol. 15(12) (2019) - [j37]Andreas Bartschat, Markus Reischl, Ralf Mikut:
Data mining tools. WIREs Data Mining Knowl. Discov. 9(4) (2019) - [j36]Frank Hoffmann, Torsten Bertram, Ralf Mikut, Markus Reischl, Oliver Nelles:
Benchmarking in classification and regression. WIREs Data Mining Knowl. Discov. 9(5) (2019) - [c22]Karl Schwenk, Manuel Faix, Ralf Mikut, Veit Hagenmeyer, Riccardo Remo Appino:
On Calendar-Based Scheduling for User-Friendly Charging of Plug-In Electric Vehicles. CAVS 2019: 1-5 - [c21]Tilman Daab, Isabel Patzer, Ralf Mikut, Tamim Asfour:
Feature Space Exploration for Motion Classification Based on Multi-Modal Sensor Data for Lower Limb Exoskeletons. Humanoids 2019: 636-643 - [c20]Jan Wachter, Ralf Mikut, Fabian Buse:
Modeling and Force Control of a Terramechanical Wheel-Soil Contact for a Robotic Manipulator Used in the Planetary Rover Design Process. IROS 2019: 560-565 - [i15]Jorge Ángel González Ordiano, Lutz Gröll, Ralf Mikut, Veit Hagenmeyer:
Probabilistic Energy Forecasting using Quantile Regressions based on a new Nearest Neighbors Quantile Filter. CoRR abs/1903.07390 (2019) - [i14]Karl Schwenk, Tim Harr, René Großmann, Riccardo Remo Appino, Veit Hagenmeyer, Ralf Mikut:
Data-driven charging strategies for grid-beneficial, customer-oriented and battery-preserving electric mobility. CoRR abs/1910.07503 (2019) - [i13]Geoffroy Chaussonnet, Christian Lieber, Yikang Yan, Wenda Gu, Andreas Bartschat, Markus Reischl, Rainer Koch, Ralf Mikut, Hans-Jörg Bauer:
Towards DeepSpray: Using Convolutional Neural Network to post-process Shadowgraphy Images of Liquid Atomization. CoRR abs/1910.11073 (2019) - 2018
- [j35]Jorge Ángel González Ordiano, Andreas Bartschat, Nicole Ludwig, Eric Braun, Simon Waczowicz, Nicolas Renkamp, Nico Peter, Clemens Düpmeier, Ralf Mikut, Veit Hagenmeyer:
Concept and benchmark results for Big Data energy forecasting based on Apache Spark. J. Big Data 5: 11 (2018) - [j34]Benjamin Schott, Manuel Traub, Cornelia Schlagenhauf, Masanari Takamiya, Thomas Antritter, Andreas Bartschat, Katharina Löffler, Denis Blessing, Jens C. Otte, Andrei Kobitski, G. Ulrich Nienhaus, Uwe Strähle, Ralf Mikut, Johannes Stegmaier:
EmbryoMiner: A new framework for interactive knowledge discovery in large-scale cell tracking data of developing embryos. PLoS Comput. Biol. 14(4) (2018) - [j33]Jorge Ángel González Ordiano, Simon Waczowicz, Veit Hagenmeyer, Ralf Mikut:
Energy forecasting tools and services. WIREs Data Mining Knowl. Discov. 8(2) (2018) - [c19]Simon Waczowicz, Nicole Ludwig, Jorge Ángel González Ordiano, Ralf Mikut, Veit Hagenmeyer:
Demand Response clustering: Automatically finding optimal cluster hyper-parameter values. e-Energy 2018: 429-430 - [c18]