Normalized Difference Vegetation Index — You Don’t Always Need Deep Learning for Satellite Imagery
March 21st, 2021

While looking for an ML solution to understand the relationship between climate change and forced displacement in Somalia, Deep Learning turned out to be non-resource-efficient. Instead, we used satellite imagery indices to understand image bands and the different combi

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7 Steps to Build a Quality Satellite Imagery Dataset for Agricultural Applications
March 14th, 2021

So, you have decided to use satellite imagery for agricultural purposes and prepare your own satellite imagery dataset? GREAT! You are in the right place.   By Jayasudan Munsamy, Alexander Epifanov, and Łukasz Murawski         Background This article

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Harnessing AI and Open Source Satellite Imagery to Address Global Problems
March 1st, 2021

Omdena successfully combines AI and ML methodologies with open source, low resolution satellite imagery to create actionable solutions for powerful insights.   Introduction Every day, millions of images are captured from space by an ever-growing number of satellite

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Crop Yield Prediction Using Deep Neural Networks and LSTM
February 28th, 2021

Crop yield prediction using deep neural networks to increase food security in Senegal, Africa. The case study covers leveraging vegetation indices with land cover satellite images from Google Earth Engine and applying deep learning models combined with ground truth data

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Using Convolutional Neural Networks To Improve Road Safety And Save Lives
February 23rd, 2021

Applying AI on satellite images for improving road safety. We used pre-trained CNNs, VGG, ResNet, and Inception models to count vehicles on roads and analyze traffic flow to help save many lives.   By Lois Anne Leal and Chaitree Sham Baradkar   The Why At nigh

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