But satellite imagery indicates that while the attacks were widespread, the damage was far more contained than claimed — and appeared mostly inflicted by India on Pakistani facilities.

What if the tools you already use could do more than you ever imagined? Picture this: you’re working on a massive dataset in Excel, trying to make sense of endless rows and columns. It’s slow ...

This is a code repository for our paper Tree species classification from airborne hyperspectral and LiDAR data using 3D convolutional neural ... tree species mapping from multispectral satellite ...

The primary contributions of this study involve: (1) an examination of the impacts of different U-Net feature levels on crop classification using 16-m resolution GF-6 WFV imagery ... Ciampitti IA ...

They decided to work with EOS Data Analytics, a California-based provider of satellite imagery and data for ... solely for agriculture. Fees to use the crop-monitoring platform now start at ...

A research team investigated the efficacy of AlexNet, an advanced Convolutional Neural Network (CNN) variant, for automatic crop classification using high-resolution aerial imagery from UAVs.

Building on a state-of-the-art architecture using self-attention to classify crops captured in satellite images time series, we introduce two changes in order to better capture the crop ... 1.0.2 The ...

Satlas’ AI modeling software improves satellite image resolution ... its line of geospatial data products to include mapping tools for urban land use, agricultural crop types and land cover.