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We invite contributions to the special issue on <b>Deep Learning
for Environmental Remote Sensing</b> in the journal <b>Sensors</b>
(IF: 3.847).<br>
<br>
<a class="moz-txt-link-freetext" href="https://www.mdpi.com/journal/sensors/special_issues/474QRK5XS0">https://www.mdpi.com/journal/sensors/special_issues/474QRK5XS0</a><br>
<br>
The submission deadline is July 26, 2023. <br>
<br>
Submitted papers are expected to be aligned with one or more of the
relevant topics of the special issue, including (but not limited
to):<br>
- deep learning models<br>
- explainable deep learning models<br>
- multimodal and multiscale remote sensing data fusion<br>
- uncertainty quantification of deep learning in environmental and
Earth observation applications<br>
- mapping, monitoring, and characterization of land cover changes
with time series<br>
- robust parameters retrieval for forestry and agricultural
applications<br>
- hybrid deep learning and physical models in environmental
applications<br>
- physical interpretation of deep learning models<br>
- application of deep learning to environmental science,
agroecology, agroforestry, water management, biodiversity assessment
and restoration, forest disturbances, natural resources mapping,
disaster management, using Earth observation data<br>
<br>
Please consider contributing to and/or forwarding this CFP to
potentially interested people.
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