GregCocks, to RadioControl
@GregCocks@techhub.social avatar

The Case For Remote Sensing Of Individual Plants

https://doi.org/10.1002/ajb2.1347 <-- shared short article

#GIS #spatial #mapping #UAV #drone #drones #LiDAR #photosynthesis #imagingspectroscopy #trees #plants #vegetation #forest #monitoring #identification #satellite #cubesat #landsurface #landcover #spatialanalysis # interpretation #biology #scale #sensor #technology #fieldwork #fieldplatforms #spatiotemporal #resources #naturalresources #phenology #photogrammetry #plantbiology #model #modeling #inference #remotesensing

aerial images - High-resolution images from the Planet Labs constellation of cube-sats detect flowering individual trees in the Peruvian Amazon (yellow objects in panel A) and Colombian Amazon (pink objects in panel B). Many thousands of flowering individuals are apparent across hundreds of kilometers of Amazonian forest in these flowering events. Scale bar = 500 m.
aerial and oblique remotesensing-created images - Drone remote sensing of individual trees. (A) Ultra-high-density drone lidar resolves individual tree structure in a temperate beech forest in the southern Czech Republic. Colors indicate elevation, and the tallest trees are about 40 m aboveground. Measurement density here is 4323 points per square meter. (B) High-spatial resolution optical remote sensing from a low-altitude drone in the Atlantic lowlands of Costa Rica. We used methods from computer vision to construct three-dimensional scene geometry from two-dimensional images. The image is a natural color composite. (C) Same area as B, but colored by surface elevation, where warmer colors indicate taller objects. A single Goethalsia meiantha crown is outlined in white. The area of this crown is 157.3 m2. At a pixel size of 1 cm, this crown contains 1.573 × 106 pixels, demonstrating the tremendous increase in measurement density at high-spatial resolution. Scale bar in B and C = 30 m.
graphic / schematic - drone performing remote sensing on a tree

SteveThompson, to random
@SteveThompson@mastodon.social avatar

"Facial recognition used after Sunglass Hut robbery led to man’s wrongful jailing, says suit"

https://www.theguardian.com/technology/2024/jan/22/sunglass-hut-facial-recognition-wrongful-arrest-lawsuit

"A 61-year-old man is suing Macy’s and the parent company of Sunglass Hut over the stores’ alleged use of a facial recognition system that misidentified him as the culprit behind an armed robbery and led to his wrongful arrest. While in jail, he was beaten and raped, according to his suit."

boilingsteam, to linux
@boilingsteam@mastodon.cloud avatar
itnewsbot, to ComputerScience
@itnewsbot@schleuss.online avatar

IBM has made a new, highly efficient AI processor - Enlarge (credit: IBM)

As the utility of AI systems has grown d... - https://arstechnica.com/?p=1977529

SteveThompson, to uk
@SteveThompson@mastodon.social avatar

"AI facial recognition: Campaigners and MPs call for ban"

https://www.bbc.com/news/technology-67022005

"Police and private companies should 'immediately stop' the use of facial recognition surveillance, says a group of politicians and privacy campaigners. They have raised concerns around human rights, potential for discrimination and 'the lack of a democratic mandate. It comes after the government announced plans for police to access passport photos to help catch criminals."

SteveThompson, to privacy
@SteveThompson@mastodon.social avatar

GOOD! A great example of 'just because we can doesn't mean we should.'

"New York bans facial recognition in schools after report finds risks outweigh potential benefits"

https://apnews.com/article/facial-recognition-banned-new-york-schools-ddd35e004254d316beabf70453b1a6a2

"New York state banned the use of facial recognition technology in schools Wednesday, following a report that concluded the risks to student privacy and civil rights outweigh potential security benefits."

kellogh, to random
@kellogh@hachyderm.io avatar

y'all are wrong, the hardest problem in computer science is not accidentally building a compiler

doboprobodyne, (edited )
@doboprobodyne@mathstodon.xyz avatar

@kellogh

I say, this made me laugh; I'd just been mulling over how models were really just , and all the that went into them was the .

Incomitatum, (edited ) to random

Many mental calories later, this is progressing.

It's all Cliche and Gimmick ;)

james, to llm

If you are curious about AI but don't have a fancy PC or graphics card, I forked and modified this repo to run a small open source from . It uses a bunch of great libraries and the CPU for .

All you need is 8 GB ram, tested on . Your mileage may vary on other OSs.

https://github.com/pingud98/mpt-7B-inference

tero, to Nvidia
@tero@rukii.net avatar

's new claims it will drop the costs of running

“You can take pretty much any you want and put it in this and it will inference like crazy.
The cost of large language models will drop significantly.”

https://www.cnbc.com/2023/08/08/nvidia-reveals-new-ai-chip-says-cost-of-running-large-language-models-will-drop-significantly-.html

archaeoriddle, to opensource

Time for our !
We are a group of researchers in at (something called ). We are challenging scientists from every fields & every level to infer what happened in an artificial world where a group of replaced a group of . Its a game, open to anyone, using any method as long as we can re-run the analysis ourself ( tools only, we won't pay a matlab licence to re-run your code 🙃 )

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