Publications per year
Publications 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):
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Dive into the research topics where Deena Francis 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
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Dimensionality reduction of large datasets with explicit feature maps
Francis, D. P., Raimond, K. & Kathrine, G. J. W., 2023, In: Intelligent Decision Technologies. 17, 2, p. 457-470Research output: Contribution to journal › Journal article › Research › peer-review
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Machine learning methods for the detection of explosives, drugs and precursor chemicals gathered using a colorimetric sniffer sensor
Francis, D. P., Laustsen, M., Dossi, E., Treiberg, T., Hardy, I., Shiv, S. H., Hansen, B. S., Mogensen, J., Jakobsen, M. H. & Alstrøm, T. S., 2023, In: Analytical Methods. 15, 19, p. 2343–2354Research output: Contribution to journal › Journal article › Research › peer-review
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Validation of Digital Twins: Challenges and Opportunities
Hua, E. Y., Lazarova-Molnar, S. & Francis, D. P., 2023, Proceedings of the 2022 Winter Simulation Conference, WSC 2022. IEEE, p. 2900-2911Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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A framework for data-driven digital twins for smart manufacturing
Friederich, J., Francis, D. P., Lazarova-Molnar, S. & Mohamed, N., 2022, In: Computers in Industry. 136, 13 p., 103586.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile1146 Downloads (Pure) -
Classification of colorimetric sensor data using time series
Francis, D. P., Laustsen, M., Babamoradi, H., Mogensen, J., Dossi, E., Jakobsen, M. H. & Alstrøm, T. S., 2021, Artificial Intelligence and Machine Learning in Defense Applications III. Dijk, J. (ed.). Washington: SPIE - International Society for Optical Engineering, Vol. 11870. 9 p. 118700L. (Proceedings of SPIE - The International Society for Optical Engineering).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Open AccessFile170 Downloads (Pure)
Projects
- 2 Active
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Machine Learning for Beehives Monitoring
Andersen, B. (PI), Francis, D. (Project Participant), You, L. (Project Participant), Ottosen, I. M. (Project Participant), Petersen, S. M. B. (Project Participant) & Pholprasit, P. (Project Participant)
01/08/2023 → 31/07/2026
Project: Research
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InnoTech - TaskForce
Andersen, B. (Project Manager), Schultz, O. (Project Participant), Rubin-Grøn, D. K. (Project Participant), Tange, H. (Project Participant), Singh, B. (Project Participant), Lynggaard, P. (Project Participant), Coelho, L. G. (Project Participant), Lund, V. (Project Participant), Grex, S. (Project Participant), Andrade, V. (Project Participant), Francis, D. (Project Participant), You, L. (Project Participant) & Christiansen, S. (Project Participant)
01/01/2023 → 31/12/2025
Project: Research