Deep Convolutional Neural Networks (DCNNs) have achieved remarkable success in various Computer Vision applications. Like others, the task of semantic segmentation is not an exception to this trend.
Source: freecodecamp.org
Recently, we discovered two exoplanets by training a neural network to analyze data from NASA’s Kepler space telescope and accurately identify the most promising planet signals. And while this was only an initial analysis of ~700 stars, we consider this a successful proof-of-concept for using machine learning to discover exoplanets, and more generally another example of using machine learning to make meaningful gains in a variety of scientific disciplines (e.g. healthcare, quantum chemistry, and fusion research)
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