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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume X-4/W2-2022
https://doi.org/10.5194/isprs-annals-X-4-W2-2022-265-2022
© Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License.
14 Oct 2022
| 14 Oct 2022
A REGION-BASED MACHINE LEARNING APPROACH FOR SELF-DIAGNOSIS OF A 4D DIGITAL THERMAL TWIN
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The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.
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