Skip to main content Skip to main navigation

Publications

Displaying results 131 to 140 of 661.

  1. Jurgen van den Hoogen; Dan Hudson; Stefan Bloemheuvel; Martin Atzmueller

    Hyperparameter analysis of wide-kernel CNN architectures in industrial fault detection: an exploratory study

    In: International Journal of Data Science and Analytics, Pages 1-22, Springer, 2023.

  2. Martin Ben Ahmed; Niklas Wilming; Martin Atzmueller

    Graph Neural Network-Based Measurement Inference on Irregular Sensor Geometries

    In: 2023 IEEE 21st International Conference on Industrial Informatics (INDIN). IEEE International Conference on Industrial Informatics (INDIN), Pages 1-8, IEEE, 2023.

  3. J.M. Górriz; I. Álvarez-Illán; A. Álvarez-Marquina; J.E. Arco; M. Atzmueller; F. Ballarini; E. Barakova; G. Bologna; P. Bonomini; G. Castellanos-Dominguez; D. Castillo-Barnes; S.B. Cho; R. Contreras; J.M. Cuadra; E. Domínguez; F. Domínguez-Mateos; R.J. Duro; D. Elizondo; A. Fernández-Caballero; E. Fernandez-Jover; M.A. Formoso; N.J. Gallego-Molina; J. Gamazo; J. García González; J. Garcia-Rodriguez; C. Garre; J. Garrigós; A. Gómez-Rodellar; P. Gómez-Vilda; M. Graña; B. Guerrero-Rodriguez; S.C.F. Hendrikse; C. Jimenez-Mesa; M. Jodra-Chuan; V. Julian; G. Kotz; K. Kutt; M. Leming; J. de Lope; B. Macas; V. Marrero-Aguiar; J.J. Martinez; F.J. Martinez-Murcia; R. Martínez-Tomás; J. Mekyska; G.J. Nalepa; P. Novais; D. Orellana; A. Ortiz; D. Palacios-Alonso; J. Palma; A. Pereira; P. Pinacho-Davidson; M.A. Pinninghoff; M. Ponticorvo; A. Psarrou; J. Ramírez; M. Rincón; V. Rodellar-Biarge; I. Rodríguez-Rodríguez; P.H.M.P. Roelofsma; J. Santos; D. Salas-Gonzalez; P. Salcedo-Lagos; F. Segovia; A. Shoeibi; M. Silva; D. Simic; J. Suckling; J. Treur; A. Tsanas; R. Varela; S.H. Wang; W. Wang; Y.D. Zhang; H. Zhu; Z. Zhu; J.M. Ferrández-Vicente

    Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends

    In: Information Fusion, Vol. 100, Pages 1-37, Elsevier, 2023.

  4. Damun Mollahassani; Martin Becker; Andreas Emrich; Peter Fettke; Jens C. Göbel

    Generating additional Engineering Knowledge in Smart Product Value Creation Networks

    In: Dimitris Mourtzis (Hrsg.). Procedia CIRP, Vol. 136 - 35th CIRP Design 2025, Pages 630-635, Elsevier, 2025.

  5. Hannes Kath; Thiago Gouvea; Daniel Sonntag

    Speeding Up Bioacoustic Data Analysis: Fine-Tuning Deep Models with Active Learning for Efficient Wildlife Detection

    In: GoodIT '25: Proceedings of the 2025 International Conference on Information Technology for Social Good. ACM International Conference on Information Technology for Social Good (GoodIT-2025), located at GoodIT-2025, September 3-5, Antwerpen, Belgium, Association for Computing Machinery, 9/2025.

  6. Francisco Mena; Diego Arenas; Andreas Dengel

    In the search for optimal multi-view learning models for crop classification with global remote sensing data

    In: International Journal of Applied Earth Observation and Geoinformation (JAG), Vol. 143, Pages 0-15, Elsevier, Empowering Smart and Sustainable Agriculture with , 9/2025.

  7. Alexander Michael Rombach; Peter Fettke

    Deep Learning Based Key Information Extraction from Business Documents: Systematic Literature Review

    In: ACM Computing Surveys (CSUR), Vol. 58, No. 2, Pages 1-37, Association for Computing Machinery, New York, NY, USA, 2025.

  8. Tianming Du; Tao Jiang; Xuanyi Li; Md Mamunur Rahaman; Marcin Grzegorzek; Chen Li

    Prediction of TP53 mutations across female reproductive system pan-cancers using deep multimodal PET/CT radiogenomics

    In: Frontiers in Medicine, Vol. 12, Pages 1608652-1608652, Frontiers Media SA, 9/2025.

  9. Shange Wang; Lin Xu; Linshuai Zhang; Yujie Zhang; Chen Li; Marcin Grzegorzek; Jing Guo; Tao Jiang

    HHBSNet: a global channel–spatial attention and multi-scale dilated convolution network for automatic melasma segmentation

    In: Frontiers in Physiology, Vol. 16 - 2025, Frontiers Media SA, 11/2025.

  10. Leonid Schwenke; Till Stückemann; Martin Atzmueller

    Evaluating Higher-Level and Symbolic Features in Deep Learning on Time Series: Towards Simpler Explainability

    In: Proc. International Work-Conference on Artificial Neural Networks. International Work-Conference on Artificial Neural Networks (IWANN), Springer, 2025.

Year

More options