Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 25
Number of items: 25
  • Open Access
    Pimentel, A., Grelck, C., Miedema, L., Sapra, D., Völp, M., Lucchetti, F., Matovic, A., Maggio, M., Vreman, N., Altmeyer, S., Haas, F., Casimiro, A., Cecílio, J., Jäger, G., Espindola, A., Skalistis, S., Kouwer, J., de Lange, G., Almeida, J., ... Novobílský, P. (2023). The ADMORPH Approach for Adaptively Morphing Embedded Systems. Ada Letters, 43(2), 78–83. https://doi.org/10.1145/3672359.3672372
  • Open Access
    Chabal, D., Sapra, D., & Mann, Z. A. (2023). On Achieving Privacy-Preserving State-of-the-Art Edge Intelligence. (v2 ed.) ArXiv. https://doi.org/10.48550/arXiv.2302.05323
  • Open Access
    Sapra, D. (2022). Efficient neural architectures for edge devices. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Sapra, D., & Pimentel, A. D. (2022). Designing convolutional neural networks with constrained evolutionary piecemeal training. Applied Intelligence, 52(15), 17103–17117. https://doi.org/10.1007/s10489-021-02679-7
  • Open Access
    Aghapour, E., Sapra, D., Pimentel, A., & Pathania, A. (2022). CPU-GPU Layer-Switched Low Latency CNN Inference. In H. Fabelo, S. Ortega, & A. Skavhaug (Eds.), 2022 25th Euromicro Conference on Digital System Design: DSD 2022 : 31 August-2 September 2022, Maspalomas, Spain : proceedings (pp. 324-331). IEEE Computer Society. https://doi.org/10.1109/DSD57027.2022.00051
  • Open Access
    Minakova, S., Sapra, D., Stefanov, T., & Pimentel, A. D. (2022). Scenario Based Run-time Switching for Adaptive CNN-based Applications at the Edge. ACM Transactions on Embedded Computing Systems, 21(2), Article 14. https://doi.org/10.1145/3488718
  • Open Access
    van Ipenburg, I., Sapra, D., & Pimentel, A. D. (2021). Exploring Cell-Based Neural Architectures for Embedded Systems. In M. Kamp, I. Koprinska, A. Bibal, T. Bouadi, B. Frénay, L. Galárraga, J. Oramas, & L. Adilova (Eds.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2021, virtual event, September 13-17, 2021 : proceedings (Vol. I, pp. 363–374). (Communications in Computer and Information Science; Vol. 1524). Springer. https://doi.org/10.1007/978-3-030-93736-2_28
  • Open Access
    Odyurt, U., Sapra, D., & Pimentel, A. D. (2021). The Choice of AI Matters: Alternative Machine Learning Approaches for CPS Anomalies. In H. Fujita, A. Selamat, JC.-W. Lin, & M. Ali (Eds.), Advances and Trends in Artificial Intelligence : From Theory to Practice: 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26–29, 2021 : proceedings (Vol. II, pp. 474-484). (Lecture Notes in Computer Science; Vol. 12799), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-79463-7_40
  • Open Access
    Sapra, D., & Pimentel, A. D. (2020). Constrained evolutionary piecemeal training to design convolutional neural networks. In H. Fujita, P. Fournier-Viger, M. Ali, & J. Sasaki (Eds.), Trends in Artificial Intelligence Theory and Applications : Artificial Intelligence Practices: 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, Kitakyushu, Japan, September 22-25, 2020 : proceedings (pp. 709-721). (Lecture Notes in Computer Science; Vol. 12144), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-55789-8_61
  • Open Access
    Sapra, D., & Pimentel, A. D. (2020). Deep Learning Model Reuse and Composition in Knowledge Centric Networking. In ICCCN 2020: the 29th International Conference on Computer Communication and Networks : final program : August 3-August 6, 2020, Honolulu, Hawaii, USA (pp. 716-726). (Proceedings International Conference on Computer Communications and Networks; Vol. 29). IEEE. https://doi.org/10.1109/ICCCN49398.2020.9209668
Page 2 of 3