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.

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 .

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.

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.

Hoseini, S., Burgdorf, A., Paulus, A., Meisen, T., Quix, C., & Pomp, A. (2024). "Towards LLM-augmented Creation of Semantic Models for Dataspaces" in The Second International Workshop on Semantics in Dataspaces, co-located with the Extended Semantic Web Conference .

Hadwiger, S., Kube, D., Lavrik, V., & Meisen, T. (2024). "Towards Precision in Motion: Investigating the Influences of Curriculum Learning based on a Multi-Purpose Performance Metric for Vision-Based Forklift Navigation" in 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE) , IEEE 796—803.

Alves Gomes, M., & Meisen, T. (2023). "A review on customer segmentation methods for personalized customer targeting in e-commerce use cases" , Information Systems and e-Business Management .

Bulow, F., & Meisen, T. (2023). "A review on methods for state of health forecasting of lithium-ion batteries applicable in real-world operational conditions" , Journal of Energy Storage , 57 , 105978.