Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 109
Number of items: 109
  • Open Access
    Groenendijk, R., Dorst, L., & Gevers, T. (2024). HaarNet: Large-Scale Linear-Morphological Hybrid Network for RGB-D Semantic Segmentation. In S. Brunetti, A. Frosini, & S. Rinaldi (Eds.), Discrete Geometry and Mathematical Morphology: Third International Joint Conference, DGMM 2024, Florence, Italy, April 15–18, 2024 : proceedings (pp. 242–254). (Lecture Notes in Computer Science; Vol. 14605). Springer. https://doi.org/10.1007/978-3-031-57793-2_19
  • Open Access
    Dorst, L. (2024). Paraxial Geometric Optics in 3D through Point-based Geometric Algebra. In B. Sheng, L. Bi, J. Kim, N. Magnenat-Thalmann, & D. Thalmann (Eds.), Advances in Computer Graphics: 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28–September 1, 2023 : proceedings (Vol. IV, pp. 340-354). (Lecture Notes in Computer Science; Vol. 14498). Springer. https://doi.org/10.1007/978-3-031-50078-7_27
  • Open Access
    Dorst, L. (2024). Projective duality encodes complementary orientations in geometric algebras. Mathematical Methods in the Applied Sciences, 47(14), 11422-11438. https://doi.org/10.1002/mma.9754
  • Open Access
    Dorst, L., & De Keninck, S. (2024). Physical Geometry by Plane-Based Geometric Algebra. In D. W. H. Araujo Da Silva, D. Hildenbrand, & E. Hitzer (Eds.), Advanced Computational Applications of Geometric Algebra: ICACGA 2022, Denver, CO, USA, October 2–5 (pp. 43–76). (Springer Proceedings in Mathematics & Statistics; Vol. 445). Springer. https://doi.org/10.1007/978-3-031-55985-3_2
  • Dorst, L. (2023). Complementary Orientations in Geometric Algebras. In E. Hitzer, G. Papagiannakis, & P. Vasik (Eds.), Empowering Novel Geometric Algebra for Graphics and Engineering : 7th International Workshop, ENGAGE 2022, virtual event, September 12, 2022 : proceedings (pp. 54-66). (Lecture Notes in Computer Science; Vol. 13862). Springer. https://doi.org/10.1007/978-3-031-30923-6_5
  • Open Access
    Groenendijk, R. W. (2023). Going into depth: Learning morphological aspects in data modalities using neural networks. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Groenendijk, R., Dorst, L., & Gevers, T. (2023). Geometric Back-Propagation in Morphological Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(11), 14045-14051. https://doi.org/10.1109/TPAMI.2023.3290615
  • Open Access
    ElNaghy, H., & Dorst, L. (2022). Pairwise Alignment of Archaeological Fragments Through Morphological Characterization of Fracture Surfaces. International Journal of Computer Vision, 130(9), 2184–2204. https://doi.org/10.1007/s11263-022-01635-3
  • Open Access
    Groenendijk, R., Dorst, L., & Gevers, T. (2022). MorphPool: Efficient Non-linear Pooling & Unpooling in CNNs. In The 33rd British Machine Vision Conference Proceedings: BMVC 2022 : 21st-24th November 2022, London, UK Article 56 BMVA Press. https://doi.org/10.48550/arXiv.2211.14037
  • Dorst, L. (2021). Optimal Combination of Orientation Measurements Under Angle, Axis and Chord Metrics. In S. Xambó-Descamps (Ed.), Systems, patterns and data engineering with geometric calculi (pp. 47-88). (SEMA SIMAI Springer series; Vol. 13), (ICIAM 2019 SEMA SIMAI Springer Series). Springer. https://doi.org/10.1007/978-3-030-74486-1_4
Page 1 of 11