Publikationen
Grundlagen
Natural Language Processing
Prof. Dr. Timo Baumann
Prof. Dr. Armin Sehr
11068376
C7MJNX9G
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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K. Kinoshita, M. Delcroix, S. Gannot, E. Habets, R. Haeb-Umbach, W. Kellermann, V. Leutnant, R. Maas, T. Nakatani, B. Raj, A. Sehr, & T. Yoshioka. (2016). A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research. EURASIP Journal on Advances in Signal Processing. https://doi.org/10.1186/s13634-016-0306-6
R. Maas, C. Huemmer, A. Sehr, & W. Kellermann. (2015). A Bayesian view on acoustic model-based techniques for robust speech recognition. EURASIP Journal on Advances in Signal Processing. https://doi.org/10.1186/s13634-015-0287-x
Mathematische Grundlagen neuronaler Netze
Prof. Dr. Martin Weiß
11068376
2ZCIKMVR
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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S. Bock, & M. G. Weiß. (2023). U-Shape Phenomenon with Gaussian Noise and Clipped Inputs. International Conference on Information and Computer Technologies (ICICT). https://doi.org/10.1007/978-981-99-3043-2_45
S. Bock, & M. G. Weiß. (2019). Non-Convergence and Limit Cycles in the Adam optimizer. 2019 International Conference on Artificial Neural Networks ICANN. https://doi.org/10.1007/978-3-030-30484-3_20
S. Bock, & M. G. Weiß. (2019). A Proof of Local Convergence for the Adam Optimizer. 2019 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN.2019.8852239
S. Townley, A. Ilchmann, M. G. Weiß, W. McClements, A. C. Ruiz, & D. Prätzel-Wolters. (2000). Existence and Learning of Oscillations in Recurrent Neural Networks. IEEE Transactions on Neural Networks. https://doi.org/10.1109/72.822523
M. G. Weiß. (1998). Learning Periodic Signals with Recurrent Neural Networks. Journal of Applied Mathematics and Mechanics. https://doi.org/10.1002/zamm.199807815130
M. G. Weiß. (1997). Learning Oscillations Using Adaptive Control. International Conference on Artificial Neural Networks (ICANN). https://doi.org/10.1007/BFb0020176
Software Engineering
Prof. Dr. Wolfgang Mauerer
Prof. Dr. Jürgen Mottok
11068376
C2U7C76X
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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W. Mauerer, S. Klessinger, & S. Scherzinger. (2022). Beyond the Badge: Reproducibility Engineering as a Lifetime Skill. SEENG@International Conference on Software Engineering (ICSE). https://doi.org/10.1145/3528231.3528359
L. Grabinger, F. Hauser, & J. Mottok. (2022). Accessing the Presentation of Causal Graphs and an Application of Gestalt Principles with Eye Tracking. In Proceedings of the 29th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2022). 29th IEEE, New York, NY, USA. https://doi.org/10.1109/SANER53432.2022.00153
W. Mauerer, M. Joblin, D. A. Tamburri, C. Paradis, R. Kazman, & Sven Apel. (2021). In Search of Socio-Technical Congruence: A Large-Scale Longitudinal Study. IEEE Transactions on Software Engineering. https://doi.org/10.1109/TSE.2021.3082074
F. Hauser, S. Schreistetter, R. Reuter, J. Mottok, H. Gruber, K. Holmqvist, & N. Schorr. (2020). Code reviews in C++: Preliminary results from an eye tracking study. Proceedings of the ACM Eye Tracking Research and Application. https://doi.org/10.1145/3379156.3391980
R. Ramsauer, L. Bulwahn, D. Lohmann, & W. Mauerer. (2020). The Sound of Silence: Mining Security Vulnerabilities from Secret Integration Channels in Open-Source Projects. Proceedings of the 12th Cloud Computing Security Workshop (CCSW ’20). https://doi.org/10.1145/3411495.3421360
W. Mauerer, & S. Scherzinger. (2020). Educating Future Software Architects in the Art and Science of Analysing Software Data. Proc. SEUH Workshop. http://ceur-ws.org/Vol-2531/paper10.pdf
R. Ramsauer, D. Lohmann, & W. Mauerer. (2019). The List is the Process: Reliable Pre-Integration Tracking of Commits on Mailing Lists. Proceedings of the 41st International Conference on Software Engineering (ICSE ’19). https://doi.org/10.1109/ICSE.2019.00088
I. Hutzler, F. Hauser, R. Reuter, J. Mottok, & H. Gruber. (2018). Will the Noun/Verb Analysis be Used to Generate Class Diagrams? An Eye Tracking Study. 11th annual International Conference of Education, Research and Innovation, Seville, Spain. https://doi.org/10.21125/iceri.2018.1103
F. Hauser, M. Reiß, M. Nivala, J. Mottok, & H. Gruber. (2017). Eye Tracking Applied: Visual Expertise in Code Reviews. International Conference on Education and New Learning Technologies, Barcelona, Spain. https://doi.org/10.21125/edulearn.2017.1084
M. Joblin, S. Apel, C. Hunsen, & W. Mauerer. (2017). Classifying Developers into Core and Peripheral: An Empirical Study on Count and Network Metrics. 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE). https://doi.org/10.1109/icse.2017.23
M. Nivala, F. Hauser, J. Mottok, & H. Gruber. (2016). Developing visual expertise in software engineering: An eye tracking study. Proceedings of the IEEE EDUCON 2016. IEEE EDUCON 2016, Abu Dhabi, UAE. https://doi.org/10.1109/EDUCON.2016.7474614
M. Joblin, S. Apel, & Wolfgang Mauerer. (2016). Evolutionary trends of developer coordination: a network approach. Empirical Software Engineering. https://doi.org/10.1007/s10664-016-9478-9
M. Joblin, W. Mauerer, S. Apel, J. Siegmund, & D. Riehle. (2015). From Developer Networks to Verified Communities: A Fine-Grained Approach. 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering. https://doi.org/10.1109/icse.2015.73
Safety & Security
Prof. Dr. Jürgen Mottok
11068376
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50
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N. Weiß, E. Pozzobon, J. Mottok, & V. Matoušek. (2021). Automated Reverse Engineering of CAN Protocols. Neural Network World. https://doi.org/10.14311/NNW.2021.31.015
A. Rudolph, S. Voget, & J. Mottok. (2018). A consistent safety case argumentation for artificial intelligence in safety related automotive systems. ERTS 2018, Toulouse, France. https://hal.science/hal-02156048
Quantum AI
Prof. Dr. Wolfgang Mauerer
11068376
94TRVK2W
1
apa
50
date
desc
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Sensorik
Prof. Dr. Rudolf Bierl
Prof. Dr. Matthias Ehrnsperger
11068376
DWMMQPEM
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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Produktion
Planung
Prof. Stefan Galka
Prof. Dr. Marcus Wagner
11068376
K6X373UN
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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A. Kaps, T. Lehrer, I. Lepenies, M. Wagner, & F. Duddeck. (2023). Multi-Fidelity Optimization of Metal Sheets Concerning Manufacturability in Deep-Drawing Processes. Structural and Multidisciplinary Optimization, 66.8. https://doi.org/10.1007/s00158-023-03631-8
T. Lehrer, P. Stocker, F. Duddeck, & M. Wagner. (2023). Comparison of Low- vs. High-Dimensional Machine Learning Approaches for Sheet Metal Drawability Assessment. Third International Conference on Computational Science and AI in Industry (CSAI). Third International Conference on Computational Science and AI in Industry (CSAI). https://doi.org/10.35096/othr/pub-6477
T. Lehrer, A. Kaps, I. Lepenies, F. Duddeck, & M. Wagner. (2023). 2S-ML: A Simulation-Based Classification and Regression Approach for Drawability Assessment in Deep Drawing. International Journal of Material Forming, 16.5. https://doi.org/10.1007/s12289-023-01770-3
F. Schmid, T. Wild, J. Schneidewind, T. Vogl, L. Schuhegger, & S. Galka. (2022). Simulation Based Approach for Reconfiguration and Ramp Up Scenario Analysis in Factory Planning. 2022 Winter Simulation Conference (WSC). 2022 Winter Simulation Conference (WSC), Singapore. https://doi.org/10.1109/WSC57314.2022.10015310
Predictive Maintenance
Prof. Dr. Markus Goldhacker
11068376
7CH59T5M
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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R. Wöstmann, P. Schlunder, F. Temme, R. Klinkenberg, J. Kimberger, A. Spichtinger, M. Goldhacker, & J. Deuse. (2020). Conception of a Reference Architecture for Machine Learning in the Process Industry. 2020 IEEE International Conference on Big Data (Big Data), 1726–1735. https://doi.org/10.1109/BigData50022.2020.9378290
Robotik und Steuerung
Prof. Dr. Martin Weiß
11068376
62AARJNV
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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M. Weiß. (2021). Optimization of Cartesian Tasks with Configuration Selection. 2nd IMA Conference on Mathematics of Robotics. https://doi.org/10.1007/978-3-030-91352-6_16
M. G. Weiß. (2019). Optimal Object Placement Using a Virtual Axis. International Symposium on Advances in Robot Kinematics. https://doi.org/10.1007/978-3-319-93188-3_14
M. G. Weiß. (2015). A Class of 6R Robots and Poses with 16 Analytical Solutions. Proceedings of the IMA Conference on Mathematics of Robotics. https://cdn.ima.org.uk/wp/wp-content/uploads/2017/12/Weiss-A-Class-of-6R-Robots-and-Poses-with-16-Analytical-Solutions.pdf
M. Kurze, M. G. Weiß, & M. Otter. (2006). Methods and Tools to Design and Test Robot Control Systems. 37th International Symposium on Robotics (ISR). https://www.researchgate.net/publication/224928821_Methods_and_Tools_to_Design_and_Test_Robot_Control_Systems
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J. Reschke. (2021). Fahrerintentionserkennung zur lichtbasierten Kommunikation mit Fußgängern. Doctoral Thesis. https://publikationen.bibliothek.kit.edu/1000140184
J. Reschke, & M. Klaußner. (2021). Explicit and Implicit Communication for Automated Vehicles. Proceedings of the 14th International Symposium on Automotive Lighting (ISAL). https://www.utzverlag.de/assets/pdf/44953dbl.pdf
J. Reschke, S. Berlitz, & C. Neumann. (2020). Personalised neural networks for a driver intention prediction: communication as enabler for automated driving. Advanced Optical Technologies, 9(6). https://doi.org/https://doi.org/10.1515/aot-2020-0035
J. Reschke, T. Höß, B. Schleyer, S. Berlitz, & C. Neumann. (2019). How Vehicles Learn to Display Symbols to Pedestrians. Proceedings of the 13th International Symposium on Automotive Lighting (ISAL). https://www.utzverlag.de/catalog/book/44817
J. Reschke, S. Prösl, M. Hamm, & C. Neumann. (2018). Assistance System for Vehicle-Pedestrian-Interaction: Deep Learning and Driver Intention Prediction. SIA VISION. https://wiki.unece.org/download/attachments/75531441/AVSR-02-16e.pdf?api=v2
Mobilitätskonzepte
Prof. Dr. Simone Weikl
Prof. Dr. Jan Dünnweber
Prof. Dr. Stefan Galka
11068376
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2609
https://rcai.de/wp-content/plugins/zotpress/
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Medizin
Survey
Prof. Dr. Christoph Palm
11068376
PDAU8R99
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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C. Palm. (2023). History, Core Concepts, and Role of AI in Clinical Medicine. In M. F. Byrne, N. Parsa, A. T. Greenhill, D. Chahal, O. Ahmad, & U. Bargci (Eds.), AI in Clinical Medicine: A Practical Guide for Healthcare Professionals. https://doi.org/10.1002/9781119790686.ch5
Medizinische Bildverarbeitung
Prof. Dr. Christoph Palm
Prof. Dr. Jürgen Frikel
11068376
NEZ97PSI
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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T. Rueckert, M. Rieder, H. Feussner, D. Wilhelm, D. Rueckert, & C. Palm. (2024). Smoke Classification in Laparoscopic Cholecystectomy Videos Incorporating Spatio-temporal Information. In A. Maier, T. M. Deserno, H. Handels, K. Maier-Hein, C. Palm, & T. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2024: Proceedings, German Workshop on Medical Image Computing, March 10-12, 2024, Erlangen (pp. 298–303). https://doi.org/10.1007/978-3-658-44037-4_78
L. A. Souza Jr., A. G.C. Pacheco, L. A. Passos, M. C. S. Santana, R. Mendel, A. Ebigbo, A. Probst, H. Messmann, C. Palm, & J. P. Papa. (2024). DeepCraftFuse: visual and deeply-learnable features work better together for esophageal cancer detection in patients with Barrett’s esophagus. Neural Computing and Applications. https://doi.org/10.1007/s00521-024-09615-z
M. Gutbrod, B. Geisler, D. Rauber, & C. Palm. (2024). Data Augmentation for Images of Chronic Foot Wounds. In A. Maier, T. M. Deserno, H. Handels, K. Maier-Hein, C. Palm, & T. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2024: Proceedings, German Workshop on Medical Image Computing, March 10-12, 2024, Erlangen (pp. 261–266). https://doi.org/10.1007/978-3-658-44037-4_71
T. Rueckert, D. Rueckert, & C. Palm. (2024). Corrigendum to “Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art” [Comput. Biol. Med. 169 (2024) 107929]. Computers in Biology and Medicine. https://doi.org/10.1016/j.compbiomed.2024.108027
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T. Rückert, D. Rückert, & C. Palm. (2024). Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art. Computers in Biology and Medicine, 169. https://doi.org/10.1016/j.compbiomed.2024.107929
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M. W. Scheppach, R. Mendel, A. Probst, S. Nagl, M. Meinikheim, H. C. Yip, L. H. S. Lau, P. Y. W. Chiu, C. Palm, H. Messmann, & A. Ebigbo. (2023). Effekt eines Künstliche Intelligenz (KI) – Algorithmus auf die Gefäßdetektion bei third space Endoskopien. Zeitschrift Für Gastroenterologie, 61. https://doi.org/10.1055/s-0043-1771980
S. Zellmer, D. Rauber, A. Probst, T. Weber, S. Nagl, S., C. Römmele, E. Schnoy, C. Palm, H. Messmann, & A. Ebigbo. (2023). Verwendung künstlicher Intelligenz bei der Detektion der Papilla duodeni major. Zeitschrift Für Gastroenterologie, 61. https://doi.org/10.1055/s-0043-1772000
M. Meinikheim, R. Mendel, A. Probst, M. W. Scheppach, S. Nagl, E. Schnoy, C. Römmele, F. Prinz, J. Schlottmann, H. Messmann, C. Palm, & A. Ebigbo. (2023). Einfluss von Künstlicher Intelligenz auf die Performance von niedergelassenen Gastroenterolog:innen bei der Beurteilung von Barrett-Ösophagus. Zeitschrift Für Gastroenterologie, 61. https://doi.org/10.1055/s-0043-1771711
T. Rückert, M. Rieder, D. Rauber, M. Xiao, E. Humolli, H. Feussner, D. Wilhelm, & C. Palm. (2023). Augmenting instrument segmentation in video sequences of minimally invasive surgery by synthetic smoky frames. International Journal of Computer Assisted Radiology and Surgery, 18, S54–S56. https://doi.org/10.1007/s11548-023-02878-2
R. Mendel, D. Rauber, & C. Palm. (2023). Exploring the Effects of Contrastive Learning on Homogeneous Medical Image Data. Bildverarbeitung Für Die Medizin 2023: Proceedings, German Workshop on Medical Image Computing, July 2- 4, 2023, Braunschweig, 128–13. https://doi.org/10.1007/978-3-658-41657-7
M. W. Scheppach, D. Rauber, J. Stallhofer, A. Muzalyova, V. Otten, C. Manzeneder, T. Schwamberger, J. Wanzl, J. Schlottmann, V. Tadic, A. Probst, E. Schnoy, C. Römmele, C. Fleischmann, M. Meinikheim, S. Miller, B. Märkl, C. Palm, H. Messmann, & A. Ebigbo. (2023). Performance comparison of a deep learning algorithm with endoscopists in the detection of duodenal villous atrophy (VA). Endoscopy, 55. https://doi.org/10.1055/s-0043-1765421
M. W. Scheppach, R. Mendel, A. Probst, D. Rauber, T. Rueckert, M. Meinikheim, C. Palm, H. Messmann, & A. Ebigbo. (2023). Real-time detection and delineation of tissue during third-space endoscopy using artificial intelligence (AI). Endoscopy, 55, S53–S54. https://doi.org/10.1055/s-0043-1765128
M. Meinikheim, R. Mendel, A. Probst, M. W. Scheppach, E. Schnoy, S. Nagl, C. Römmele, F. Prinz, J. Schlottmann, D. Golger, C. Palm, H. Messmann, & A. Ebigbo. (2023). AI-assisted detection and characterization of early Barrett’s neoplasia: Results of an Interim analysis. Endoscopy, 55. https://doi.org/10.1055/s-0043-1765437
M. W. Scheppach, D. Rauber, J. Stallhofer, A. Muzalyova, V. Otten, C. Manzeneder, T. Schwamberger, J. Wanzl, J. Schlottmann, V. Tadic, A. Probst, E. Schnoy, & C. Palm. (2023). Detection of duodenal villous atrophy on endoscopic images using a deep learning algorithm. Gastrointestinal Endoscopy. https://doi.org/10.1016/j.gie.2023.01.006
R. Mendel, D. Rauber, L. A. de Souza Jr., J. P. Papa, & C. Palm. (2023). Error-Correcting Mean-Teacher: Corrections instead of consistency-targets applied to semi-supervised medical image segmentation. Computers in Biology and Medicine. https://doi.org/10.1016/j.compbiomed.2023.106585
A. Ebigbo, R. Mendel, M. W. Scheppach, A. Probst, N. Shahidi, F. Prinz, C. Fleischmann, C. Römmele, S. K. Gölder, G. Braun, D. Rauber, T. Rückert, L. A. de Souza Jr., J. P. Papa, M. Byrne, C. Palm, & H. Messmann. (2022). Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm. Gut. https://doi.org/10.1136/gutjnl-2021-326470
C. Römmele, R. Mendel, C. Barrett, H. Kiesl, D. Rauber, T. Rückert, L. Kraus, J. Heinkele, C. Dhillon, B. Grosser, F. Prinz, J. Wanzl, C. Fleischmann, S. Nagl, E. Schnoy, J. Schlottmann, E. S. Dellon, H. Messmann, C. Palm, & A. Ebigbo. (2022). An artificial intelligence algorithm is highly accurate for detecting endoscopic features of eosinophilic esophagitis. Scientific Reports. https://doi.org/10.1038/s41598-022-14605-z
L. A. de Souza Jr., R. Mendel, S. Strasser, A. Ebigbo, A. Probst, H. Messmann, J. P. Papa, & C. Palm. (2021). Convolutional Neural Networks for the evaluation of cancer in Barrett’s esophagus: Explainable AI to lighten up the black-box. Computers in Biology and Medicine. https://doi.org/10.1016/j.compbiomed.2021.104578
J. Arribas, G. Antonelli, L. Frazzoni, L. Fuccio, A. Ebigbo, F. v. d. Sommen, N. Ghatwary, C. Palm, M. Coimbra, F. Renna, J. J. G. H. M. Bergman, P. Sharma, H. Messmann, C. Hassan, & M. J. Dinis-Ribeiro. (2021). Standalone performance of artificial intelligence for upper GI neoplasia: a meta-analysis. Gut. https://doi.org/10.1136/gutjnl-2020-321922
R. Mendel, L. A. de Souza Jr., D. Rauber, J. P. Papa, & C. Palm. (2020). Semi-supervised Segmentation Based on Error-Correcting Supervision. European Conference on Computer Vision (ECCV). https://doi.org/10.1007/978-3-030-58526-6_9
A. Ebigbo, R. Mendel, A. Probst, J. Manzeneder, F. Prinz, L. A. de Souza Jr., J. P. Papa, C. Palm, & H. Messmann. (2020). Real-time use of artificial intelligence in the evaluation of cancer in Barrett’s oesophagus. Gut. https://doi.org/10.1136/gutjnl-2019-319460
A. Ebigbo, R. Mendel, T. Rückert, L. Schuster, A. Probst, J. Manzeneder, F. Prinz, M. Mende, I. Steinbrück, S. Faiss, D. Rauber, L. A. de Souza Jr., J. P. Papa, P. Deprez, T. Oyama, A. Takahashi, S. Seewald, P. Sharma, M. F. Byrne, … H. Messmann. (2020). Endoscopic prediction of submucosal invasion in Barrett’s cancer with the use of Artificial Intelligence: A pilot Study. Endoscopy. https://doi.org/10.1055/a-1311-8570
Digitale Modelle des Körpers
Prof. Dr. Sebastian Dendorfer
Prof. Dr. Lars Krenkel
Prof. Dr. Christoph Palm
11068376
B6XJ7VVG
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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Neuroimaging/Brain Computer Interface
Prof. Dr. Markus Goldhacker
11068376
F4D9IJDK
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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Ethische, rechtliche und soziale Aspekte
Empirische Sozialforschung
Prof. Dr. Sonja Haug
11068376
8FIZ6QUK
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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Ethik und Technikfolgen
Prof. Dr. Thomas Kriza
Prof. Dr. Karsten Weber
11068376
R6ZP5M5T
1
apa
50
date
desc
2609
https://rcai.de/wp-content/plugins/zotpress/
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