Sebastian Bickel

Friedrich-Alexander-Universität Erlangen-Nürnberg — Germany

Engineering · Physical Sciences

8h-index142citations18works3.32yr avg
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Research Topics

Manufacturing Process and Optimization(12), Industrial Vision Systems and Defect Detection(4), BIM and Construction Integration(3), 3D Surveying and Cultural Heritage(3), 3D Shape Modeling and Analysis(2)

Publications18 total

Symbol Detection in Mechanical Engineering Sketches: Experimental Study on Principle Sketches with Synthetic Data Generation and Deep Learning
Applied Sciences·2024· 9 citedOpen Access
Integration of product development data for further ontological utilization
Proceedings of the Design Society·2024· 4 citedOpen Access
Challenges in the Virtual Geometry Assurance of Proton Exchange Membrane Fuel Cell Stacks
Procedia CIRP·2024Open Access
Testing the Generalizability of Deep Learning Based Plausibility Detection with Unknown Finite Element Simulations
2024Open Access
Detection of Singularities in Finite Element Simulations: A 3D Deep Learning Approach
2023
FROM SKETCHES TO GRAPHS: A DEEP LEARNING BASED METHOD FOR DETECTION AND CONTEXTUALISATION OF PRINCIPLE SKETCHES IN THE EARLY PHASE OF PRODUCT DEVELOPMENT
Proceedings of the Design Society·2023· 4 citedOpen Access
Detection of Plausibility and Error Reasons in Finite Element Simulations with Deep Learning Networks
Algorithms·2023· 2 citedOpen Access
Generating Digital Twins for Path-Planning of Autonomous Robots and Drones Using Constrained Homotopic Shrinking for 2D and 3D Environment Modeling
Applied Sciences·2022· 17 citedOpen Access
A Novel Shape Retrieval Method for 3D Mechanical Components Based on Object Projection, Pre-Trained Deep Learning Models and Autoencoder
Computer-Aided Design·2022· 27 citedOpen Access
Enabling Initial Design-Checks of Parametric Designs Using Digital Engineering Methods
Proceedings of the Design Society·2022· 2 citedOpen Access
A New Projection Based Method for the Classification of Mechanical Components Using Convolutional Neural Networks
Proceedings of the Design Society·2022· 2 citedOpen Access
Resnet networks for plausibility detection in finite element simulations
2022· 1 citedOpen Access
DETECTION AND CLASSIFICATION OF SYMBOLS IN PRINCIPLE SKETCHES USING DEEP LEARNING
Proceedings of the Design Society·2021· 8 citedOpen Access
A function-oriented surface reconstruction framework for reverse engineering
CIRP Annals·2021· 15 cited
Comparing CAD part models for geometrical similarity: A concept using machine learning algorithms
Procedia CIRP·2021· 24 citedOpen Access
Approach and application to transfer heterogeneous simulation data from finite element analysis to neural networks
Journal of Computational Design and Engineering·2020· 9 citedOpen Access
How Do Digital Engineering and Included AI Based Assistance Tools Change the Product Development Process and the Involved Engineers
Proceedings of the ... International Conference on Engineering Design·2019· 13 citedOpen Access
Methodology for plausibility checking of structural mechanics simulations using deep learning on existing simulation data
2018· 5 cited

Frequent Co-authors

Sandro Wartzack(17), Benjamin Schleich(10), Stefan Goetz(6), Tobias C. Spruegel(3), Christopher Sauer(2), Martin Denk(1), Patrick Steck(1), Stefan Götz(1), Harald Völkl(1), Yifan Qie(1), Nabil Anwer(1), Richard Rothfelder(1), Andreas Grauf(1), Jessica Pickel(1), Benjamin Gerschütz(1), Martin Roth(1), Goetz Stefan(1), Wartzack Sandro(1)