@sweetd.drones
16 posts
@sweetd.drones
@DronesSweetd
Hard candy shell, soft and squishy on the inside. GIS, sUAS student
เข้าร่วม Haziran 2021
80 กำลังติดตาม4 ผู้ติดตาม
@sweetd.drones รีทวีตแล้ว
Amazing rainbow waterfall captured by photographer Greg Harlow.
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It's a Friday in December. You're looking for the perfect gift for the geo-curious on your holiday list. What better choice than our 2022 calendar? Your recipient will enjoy maps like this July map from @GeospatialJess and many more!
Order at lulu.com/en/us/shop/var…
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@sweetd.drones รีทวีตแล้ว
This is the moment that thousands of bees that survived the La Palma eruption,buried in thick ash for 50 days, were found alive
600 metres from the volcano, and surviving by sealing their hives with bee glue called propolis
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Out on the Ribbon Reefs of the #GreatBarrierReef, this is the unimaginatively named Ribbon 5. There are 356 #drone images contributing to this orthomosaic with satellite imagery in the background to show the considerable difference in spatial resolution.
data.geonadir.com/project-detail…
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@sweetd.drones รีทวีตแล้ว
Big shoreline change - this isn't just debris, it's been cut away, and more #mangrove dieback. Kewarra Beach, Queensland Australia #GeoNadir
What stories can #nadir #drone imagery tell about your local environment?
geonadir.com
#EarthObservation #geospatial #UAS
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@sweetd.drones รีทวีตแล้ว
5 Saildrone Explorers are sailing from San Francisco Bay to the S-MODE study site. The #saildrones will measure a vast array of factors incl ocean currents, wind speed and direction, air and water temperature, salinity, dissolved oxygen, and chlorophyll content 👏🔬
NASA Earth@NASAEarth
⚓️ Field research, ahoy! @NASA’s S-MODE mission has taken to the sea and sky west of San Francisco to study how small ocean whirlpools and eddies move heat, nutrients, oxygen, and carbon from the ocean surface to the deeper ocean layers below. go.nasa.gov/3pCdp4H
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@sweetd.drones รีทวีตแล้ว
"CPU based computing took 42 minutes to train over 2000 images for one epoch, while GPU based computing only took 33 SECONDS!" Click the link to find out why.
#computing #machinelearning #deeplearning
linkedin.com/pulse/gpu-vs-c…
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