Multi-Task Deep Learning for Joint Depth-Map Reconstruction and Iso-Point Prediction from Hyperspectral Images of Turbid Phantoms

Martin Hohmann

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DOI: 10.3390/s26206381
Published: 2026-10-09
Container: Sensors
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/s26206381,
  title = {Multi-Task Deep Learning for Joint Depth-Map Reconstruction and Iso-Point Prediction from Hyperspectral Images of Turbid Phantoms},
  author = {Martin Hohmann},
  year = {2026},
  journal = {Sensors},
  doi = {10.3390/s26206381},
  url = {https://doi.org/10.3390/s26206381}
}

RIS

TY  - JOUR
TI  - Multi-Task Deep Learning for Joint Depth-Map Reconstruction and Iso-Point Prediction from Hyperspectral Images of Turbid Phantoms
AU  - Martin Hohmann
PY  - 2026
JO  - Sensors
DO  - 10.3390/s26206381
UR  - https://doi.org/10.3390/s26206381
ER  -

APA

Hohmann, M. (2026). Multi-Task Deep Learning for Joint Depth-Map Reconstruction and Iso-Point Prediction from Hyperspectral Images of Turbid Phantoms. Sensors. https://doi.org/10.3390/s26206381

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crossref · retrieved 2026-11-10T08:03:14.827Z