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Tousside, B., Frochte, J., & Meisen, T. (2024). "CNNs Sparsification and Expansion for Continual Learning" in Proceedings of the 16th International Conference on Agents and Artificial Intelligence , SciTePress - Science and and Technology Publications 110—120.

Puiseau, C. W. d., Wolz, F., Montag, M., Peters, J., Tercan, H., & Meisen, T. (2024). Decision Transformer for Enhancing Neural Local Search on the Job Shop Scheduling Problem.

Hütten, N., Alves Gomes, M., Hölken, F., Andricevic, K., Meyes, R., & Meisen, T. (2024). "Deep Learning for Automated Visual Inspection in Manufacturing and Maintenance: A Survey of Open- Access Papers" , Applied System Innovation , 7 (1),

Weiss, M., Brierley, N., Schmid, M., & Meisen, T. (2024). "End-To-End Deep Learning Material Discrimination Using Dual-Energy LINAC-CT" , e-Journal of Nondestructive Testing , 29 (3),

Mack, N. A., Schümmer, F., Rose, M., & Tobias, M. (2024). "Evaluating Text Placement in Information-Rich Virtual Environments: A User Study on Controller-Anchored Text" in Nordic Conference on Human-Computer Interaction , New York, NY, USA : ACM 1—10.

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Busch, D., Freeman, I., Meyes, R., & Meisen, T. (2024). "Improved Single Camera BEV Perception Using Multi-Camera Training" in 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) , IEEE 3982—3988.

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.

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. F., 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 CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management , Serra, Edoardo and Spezzano, Francesca, Eds. New York, United States : Association for Computing Machinery