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20102025

Research activity per year

Personal profile

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  3. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  4. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

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Dive into the research topics where Sana Jabbar is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years

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  • Structural-Constrained Corner Point Prediction for Building Footprint Extraction

    Rasool, F., Jabbar, S. & Taj, M., 2025, In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18, p. 22726-22742 17 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access
  • Stereoential Net: Deep Network for Learning Building Height Using Stereo Imagery

    Jabbar, S. & Taj, M., 2024, Neural Information Processing - 30th International Conference, ICONIP 2023, Proceedings. Luo, B., Cheng, L., Wu, Z.-G., Li, H. & Li, C. (eds.). Springer Science and Business Media Deutschland GmbH, p. 478-489 12 p. (Communications in Computer and Information Science; vol. 1967 CCIS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Scopus citations
  • Stereollax Net: Stereo Parallax-Based Deep Learning Network for Building Height Estimation

    Jabbar, S. & Taj, M., 2024, In: IEEE Transactions on Geoscience and Remote Sensing. 62, p. 1-12 12 p., 5619012.

    Research output: Contribution to journalArticlepeer-review

    2 Scopus citations
  • Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge

    Martin-Isla, C., Campello, V. M., Izquierdo, C., Kushibar, K., Sendra-Balcells, C., Gkontra, P., Sojoudi, A., Fulton, M. J., Arega, T. W., Punithakumar, K., Li, L., Sun, X., Al Khalil, Y., Liu, D., Jabbar, S., Queiros, S., Galati, F., Mazher, M., Gao, Z. & Beetz, M. & 20 others, Tautz, L., Galazis, C., Varela, M., Hullebrand, M., Grau, V., Zhuang, X., Puig, D., Zuluaga, M. A., Mohy-Ud-Din, H., Metaxas, D., Breeuwer, M., Van Der Geest, R. J., Noga, M., Bricq, S., Rentschler, M. E., Guala, A., Petersen, S. E., Escalera, S., Palomares, J. F. R. & Lekadir, K., 1 Jul 2023, In: IEEE Journal of Biomedical and Health Informatics. 27, 7, p. 3302-3313 12 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    70 Scopus citations
  • Multi-view SA-LA Net: A Framework for Simultaneous Segmentation of RV on Multi-view Cardiac MR Images

    Jabbar, S., Bukhari, S. T. & Mohy-ud-Din, H., 2022, Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge - 12th International Workshop, STACOM 2021, Held in Conjunction with MICCAI 2021, Revised Selected Papers. Puyol Antón, E., Young, A., Suinesiaputra, A., Pop, M., Martín-Isla, C., Sermesant, M., Camara, O. & Lekadir, K. (eds.). Springer Science and Business Media Deutschland GmbH, p. 277-286 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13131 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    5 Scopus citations