Ülkedeki düşük zekalı büyük bir grup trafik cezalarının ceza olduğunun farkında bile değil. Adam emniyet şeridinden gitmek 20 bin olur mu diye ağlıyor. Ödediği cezayı emniyet şeridi kullanma ücreti falan sanıyor. Bu kadar zam olur mu diye isyan ediyor. Emniyet şeridinden gitmenin suç olabileceği ihtimalini bile düşünmüyor. Kırmızı ışık cezasını kırmızı ışıkta geçme önceliği ücreti sanıyor. Ehliyetsiz veya alkollü olarak cüzi bir ücret ödeyerek trafiğe çıkabileceğini düşünüyor. Hız cezası ceza değil hızlı gitme ücreti mesela. Parasını veren basabilir.
Today, we're introducing AlphaEarth Foundations from @GoogleDeepMind , an AI model that functions like a virtual satellite which helps scientists make informed decisions on critical issues like food security, deforestation, and water resources. AlphaEarth Foundations provides a powerful new lens for understanding our planet by solving two major challenges: data overload and inconsistent information.
1️⃣ It combines information from dozens of sources to analyze the world's land and coastal waters in 10x10 meter squares, allowing for remarkable precision while tracking changes over time.
2️⃣ The system's key innovation is creating a highly compact summary for each square. These summaries require 16x less storage than those produced by other AI systems and enables scientists to create detailed, consistent maps of our planet, on-demand.
AlphaEarth Foundations represents a significant step forward in understanding the state and dynamics of our changing planet. 🌎🌎🌎
Marvelous vintage map “Turkey at the Crossroads” (Time Magazine, 20 December 1943). I always enjoy maps showing the world from a country’s unique perspective.
Practice lots of ML and Data Science related Leetcode problems which is sorted properly in this website.
Visit & start practicing.
Link: https://t.co/VABquMnRDz
Prof. Dr. Behçet Yalın Özkara: "Trafikte bekliyorum, arabanın biri gelip önüme giriyor.
Bir yerde duruyorum, ceza yiyorum. Başkası kaldırıma çıkıyor, ceza yok.
Borçlarımı zamanında ödüyorum, af geliyor ödemeyen kâra geçiyor.
Mal gibi hissediyorum." https://t.co/Sl7o69r1UE
🌳 Did you know? Türkiye🇹🇷 lost over 1,000,000 hectares of forest 2001-2023, a staggering 7.4% of its 2000 forest cover of 14 million hectares! Meanwhile, it regained an estimated 1.2% of its 2000 cover between 2001-2012. Can you spot the most affected areas on my new map?
Excited to share our publication in 𝘙𝘦𝘮𝘰𝘵𝘦 𝘚𝘦𝘯𝘴𝘪𝘯𝘨 𝘰𝘧 𝘌𝘯𝘷𝘪𝘳𝘰𝘯𝘮𝘦𝘯𝘵, focused on automated road mapping in tropical forests with satellite imagery and AI.
PAPER: https://t.co/qiSEeFJf9P
Explore the power of interactive maps within your Jupyter Notebooks with the new ipyopenlayers library! Discover how this tool integrates OpenLayers, bringing your geospatial data to life. Read more in our latest blog post! https://t.co/8w3netSHYS
🚨New Comment in @NatComputSci !!
Following our open human mobility data in @ScientificData, we wrote a Comment arguing for more open and standardized human mobility datasets.
w/ @luca_msl @brulepri@martikagv@estebanmoro and Kota Tsubouchi (Yahoo)
https://t.co/KE23EQevzM
In recursive neural networks, the rate of convergence is highly correlated with the prediction accuracy. We exploit this insight in a paper to be presented at ICML to predict uncertainty. https://t.co/1qjb8ikoSD
#deeplearning#computervision
Very interesting ICLR **tiny** paper: https://t.co/CcSTmFuAyp
It computes a loss for all possible subsets of the dataset at the same time which has a very elegant solution: softplus of the negative log likelihood per sample, which essentially drops outliers 🤯
@mtetelman
🎉 Great news for the #GIS and #Jupyter communities! The @ESA is funding a project by @QuantStack and @simula_research to bring collaborative editing to GIS workflows in JupyterLab. Let's explore new ways of working with geospatial data! 🚀 https://t.co/LGtjSVNHgo
Delighted to showcase my latest work: a 3D land cover map of Turkiye. Created with the Esri dataset, it highlights the country's rich landscapes and land classes.
Map enthusiasts, check out my tutorial for tips and start mapping: https://t.co/aN9lD5ezfm
My "Mastering #GDAL Tools" course is now available on YouTube! This course is the result of my 20 years of experience processing large volumes of imagery and building data pipelines. Check out the playlist at https://t.co/B54RUesTWo . More in the thread below (1/n)
@dafajonn@bindureddy I think the point would be the resource efficiency of it. If it can run on a raspberry pie like this without a GPU, this can hit the GPU need for sure: https://t.co/upparUaQjE
We collaborated with the European Space Agency to open-source the largest ever earth observation dataset: Major TOM Core!
About half of the entire planet is covered. That's 2,245,886 patches of 1068 x 1068 pixels. At 10m resolution, we've got 256 million square km with over 2.5 trillion pixels.
More datasets from different satellites are in preparation and anyone can join this collaborative effort thanks to their organization on Hugging Face: https://t.co/5KSUdOS0E4.
Quoting @mikonvergence@esa: “democratizing Earth Observation model development and deployment with transparent, reproducible, and traceable tools - starts with the data!”
You can explore the data here https://t.co/CmpuOrRop7 & access the dataset here: https://t.co/nddBjXtV45
🚨RECORD-BREAKING 🌍EO DATASET in partnership with @huggingface
Introducing 🗺️MajorTOM-Core: the largest ML-ready Sentinel-2 dataset🤯
We tried to cover... every single point on Earth captured by @esa@CopernicusEU Sentinel-2, and we got pretty close!
More info in thread 🧵
Our new paper, co-authored with Ergin Tari and Ulaş Bağcı (@ulasbagci), "AI powered road network prediction with fused low-resolution satellite imagery and GPS trajectory", is now available online. We conducted a comprehensive analysis comparing early and late fusion of...