This research continues, but now some researchers use techniques like convolutional neural networks that enable the algorithm to develop its own features. Previous research has employed computer vision techniques with handcrafted features such as light and shadow patterns, circle finding, or edge detection. Automated crater detection algorithms have attempted to speed up this process. Crater counting started with hand counting hundreds, thousands, or even millions of craters in order to determine the age of geological units on planetary bodies of the solar system. Convolutional Neural Networks (CNN) offer promising opportunities to automatically glean scientifically relevant information directly from annotated images, without needing to handcraft features for detection.
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