Detecting Weeds Through YolactEdge Instance Segmentation to Support Smart Farming
March 24th, 2021

By Thomas Joseph, Marjan Ghobadian Introduction In order to reach the precise classification and location of crop and weeds for smart farming, several methods such as instance and semantic segmentation are applied. The target is to reach not only high accuracy regarding

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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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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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Building a Crop Yield Prediction App in Senegal Using Satellite Imagery and Jupyter
February 25th, 2021

A team of 30 AI engineers used GEE images and Jupyter to build an app for crop yield prediction in Senegal, Africa, and improve agriculture and food security in the country. By Praveen Kanna   Why In this Omdena AI Challenge with the Global Partnership for Sustaina

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