Publikationen des TMDT
- 2024
- Langer, T., Meyes, R., & Meisen, T. (2024). "Guided Exploration of Industrial Sensor Data" , Computer Graphics Forum , 43 (1),
- Busch, D., Freeman, I., Meyes, R., & Meisen, T. (2024). Improved Single Camera BEV Perception Using Multi-Camera Training.
- Paulus, A., Hölken, F., Chmielewski, S., & Pomp, A. (2024). "IoT4H: Datengewinnung und -nutzung für innovative Geschäftsmodelle im Handwerk" , HMD Praxis der Wirtschaftsinformatik , 61 (6), 1540—1550.
- Alves Gomes, M., Meyes, R., Meisen, P., & Meisen, T. (2024). "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 , 19 (1), 135—151.
- Zoghian, P. M., Oberhoff, T., Gölzhäuser, P., Großner, M., Jäkel, J., & Klemt-Albert, K. (2024). "Künstliche Intelligenz zur semantischen Extraktion von Bestandsdokumenten der Bauwirtschaft" in Künstliche Intelligenz im Bauwesen , 361—374.
ISBN: 978-3-658-42795-5
- Müller, N., Reermann, J., & Meisen, T. (2024). "Navigating the Depths: A Comprehensive Survey of Deep Learning for Passive Underwater Acoustic Target Recognition" , IEEE Access , 12 , 154092—154118.
- Stillger, F., Hasecke, F., & Meisen, T. (2024). Principal Component Clustering for Semantic Segmentation in Synthetic Data Generation.
- Hahn, Y., Maack, R., Buchholz, G., Purrio, M., Angerhausen, M., Tercan, H., & Meisen, T. (2024). "Quality Prediction in Arc Welding: Leveraging Transformer Models and Discrete Representations from Vector Quantised—VAE" in Proceedings of the 33st ACM International Conference on Information & Knowledge Management .
ISBN: 979-8-4007-0436-9
- Jantunen, M., Meyes, R., Kurchyna, V., Meisen, T., Abrahamsson, P., & Mohanani, R. (2024). "Researchers' Concerns on Artificial Intelligence Ethics: Results from a Scenario-Based Survey" in Proceedings of the 7th ACM/IEEE International Workshop on Software-intensive Business , New York, NY, USA : ACM 24—31.
ISBN: 9798400705717
- Weiss, M., & Meisen, T. (2024). "Reviewing Material-Sensitive Computed Tomography: From Handcrafted Algorithms to Modern Deep Learning" , NDT , 2 (3), 286—310.
- Weiss, M., Brierley, N., Schmid, M., & Meisen, T. (2024). "Simulation Study: Data-Driven Material Decomposition in Industrial X-ray Computed Tomography" , NDT , 2 (1), 1—15.
- Brune, M., Meisen, T., & Pomp, A. (2024). "Survey of Deep Learning-Based Methods for FMCW Radar Odometry and Ego-Localization" , Applied Sciences , 14 (6), 2267.
- Bohn, C., Freeman, I., Tercan, H., & Meisen, T. (2024). Task Weighting through Gradient Projection for Multitask Learning.
- Hahn, Y., Kienitz, P., Wönkhaus, M., Meyes, R., & Meisen, T. (2024). "Towards Accurate Flood Predictions: A Deep Learning Approach Using Wupper River Data" , Water , 16 (23),
- Alves-Gomes, M., Meisen, P., & Meisen, T. (2024). Towards Lifelong Learning Embeddings: An Algorithmic Approach to Dynamically Extend Embeddings.