A new era for Satellite Imagery by using Machine Learning

AI and Machine Learning would revolutionize our existing technological frameworks and introduce a brand new industrial age by reorienting and reworking everything from the only of appliances to cars. However, that’s not all! The applications of Machine Learning aren't solely restricted to the terrestrial zone, however, have reached for the sky too, each virtually furthermore as figuratively. Similar to all alternative domains that are constantly reimagining themselves and girding for the longer term, the domain of remote sensing is additionally undergoing profound changes and witnessing increasing use of specified algorithms once huge information and Cloud Computing became virtually omnipresent.

Machine Learning algorithms have verified to be a strong tool for analyzing satellite imagery of any resolution and proving higher and additional nuanced insights. In its emerging stages, there are a few challenges as well in the application of Machine Learning on satellite pictures, including the extraordinarily large file size of satellite mental imagery and data format being exclusively designed for geo-referenced pictures that build huge knowledge and Machine Learning applications quite tough. Though, by distinctive the utility and worth and coming up with a specially crafted answer allows the event of programs to beat these limitations.

Earth Observation giants like DigitalGlobe and Planet conjointly extensively use Machine Learning for satellite imagery. Planet has a dedicated solution for Machine Learning known as Planet Analytics that uses Machine Learning algorithms for processing of daily satellite imagery, detection and classifying objects, locating topographic and geographical features and consistently monitoring even the minutest change over time. The data feed is seamlessly integrated into the workflows and offers dazzling insights on nearly anywhere in the world.

Satellite imagery refining start-up Descartes Lab has a cloud-based platform that applies Machine Learning forecasting models to petabytes of satellite imagery that is drawn from a number of sources. Mathematician Labs has an experience applying Machine Learning to Earth Observation satellite imagery. Before machine learning will extract valuable data from imagery, the information has got to be pre-processed to line up pixels and proper for variable part conditions and spectral calibrations.

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8th Global Summit on Artificial Intelligence and Neural Networks

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