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Matasoft<p>Mistral 7B excels at everyday reasoning while OLMo2 7B shines in knowledge-intensive tasks. See how both perform in our (Un)Perplexed Spready software in our latest comparison! <a href="https://matasoft.hr/qtrendcontrol/index.php/un-perplexed-spready/un-perplexed-spready-various-articles/146-comparative-analysis-of-mistral-7b-and-olmo2-7b-on-the-ollama-platform" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">matasoft.hr/qtrendcontrol/inde</span><span class="invisible">x.php/un-perplexed-spready/un-perplexed-spready-various-articles/146-comparative-analysis-of-mistral-7b-and-olmo2-7b-on-the-ollama-platform</span></a><br> <a href="https://mastodon.world/tags/AIPowered" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AIPowered</span></a> <a href="https://mastodon.world/tags/ModelComparison" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ModelComparison</span></a> <a href="https://mastodon.world/tags/BusinessIntelligence" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BusinessIntelligence</span></a></p>
💧🌏 Greg Cocks<p>Integrated Topographic Corrections Improve Forest Mapping Using Landsat Imagery<br>--<br><a href="https://doi.org/10.1016/j.jag.2022.102716" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1016/j.jag.2022.102</span><span class="invisible">716</span></a> &lt;-- shared 2022 paper<br>--<br>“HIGHLIGHTS:<br> • [They] evaluated the impacts of topographic correction on forest mapping in the mountains.<br> • The enhanced C-correction and the physical model reduced topographic effects.<br> • The corrected Landsat imagery time series resulted in higher accuracy.<br> • Terrain information improved classification but not as much as topographic correction.<br> • [They] recommend using topographic correction for forest cover mapping..."<br><a href="https://techhub.social/tags/GIS" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GIS</span></a> <a href="https://techhub.social/tags/spatial" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatial</span></a> <a href="https://techhub.social/tags/AtmosphericCorrection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AtmosphericCorrection</span></a> <a href="https://techhub.social/tags/IlluminationCondition" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>IlluminationCondition</span></a> <a href="https://techhub.social/tags/LandCover" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LandCover</span></a> <a href="https://techhub.social/tags/ModelComparison" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ModelComparison</span></a> <a href="https://techhub.social/tags/TimeSeries" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>TimeSeries</span></a> <a href="https://techhub.social/tags/TopographicCorrection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>TopographicCorrection</span></a> <a href="https://techhub.social/tags/remotesensing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>remotesensing</span></a> <a href="https://techhub.social/tags/comparasion" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>comparasion</span></a> <a href="https://techhub.social/tags/topographic" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>topographic</span></a> <a href="https://techhub.social/tags/correction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>correction</span></a> <a href="https://techhub.social/tags/NDVI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>NDVI</span></a> <a href="https://techhub.social/tags/forest" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>forest</span></a> <a href="https://techhub.social/tags/vegetation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>vegetation</span></a> <a href="https://techhub.social/tags/model" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>model</span></a> <a href="https://techhub.social/tags/modeling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>modeling</span></a> <a href="https://techhub.social/tags/spatialanalyis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatialanalyis</span></a> <a href="https://techhub.social/tags/accuracy" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>accuracy</span></a> <a href="https://techhub.social/tags/forestcover" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>forestcover</span></a> <a href="https://techhub.social/tags/Russia" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Russia</span></a> <a href="https://techhub.social/tags/Georgia" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Georgia</span></a> <a href="https://techhub.social/tags/CaucasusMountains" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CaucasusMountains</span></a> <a href="https://techhub.social/tags/spatiotemporal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatiotemporal</span></a> <a href="https://techhub.social/tags/landsat" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>landsat</span></a> <a href="https://techhub.social/tags/elevation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>elevation</span></a> <a href="https://techhub.social/tags/DEM" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DEM</span></a></p>
Dr Mircea Zloteanu 🌼🐝<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statstab</span></a> #51 R Functions for Variance Decomposition {varde}</p><p>Thoughts: A useful package to get more insight into your mixed effects model.</p><p><a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>r</span></a> <a href="https://mastodon.social/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>rstats</span></a> <a href="https://mastodon.social/tags/mixedeffects" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mixedeffects</span></a> <a href="https://mastodon.social/tags/lmm" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>lmm</span></a> <a href="https://mastodon.social/tags/research" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>research</span></a> <a href="https://mastodon.social/tags/modelcomparison" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>modelcomparison</span></a> </p><p><a href="https://github.com/jmgirard/varde" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">github.com/jmgirard/varde</span><span class="invisible"></span></a></p>