Good morning, a couple of months ago I started a demo for a project that I have been thinking about for a long time, how to use technology to help find habitable planets that are in star systems, moving around their companion star. Something not very ambitious, the truth.

For this I had thought to try to detect the moment when that planet is right between the earth and its companion star, so that if when we see the light of that star when there is nothing between it and us, it is represented as a continuous line , because we always get the same amount of light, when a possible planet is right between us and its companion star, the graph of light represents the characteristic form of a letter or a bell.

The case is that to reach that point, first you have to find these stars and that is the basis for this first approach to write a software, something that is absolutely necessary, to classify the stars that can be found from images obtained by astronomers after spend many days and nights capturing them with their cameras and mirrors. From here, I want to thank the person who helped me by providing me with a set of images to train and test a model based on convolutional neural networks using the deeplearning4j framework, Ramon Naves. Thank you very much Ramón.

The project is in its initial phases, basically I took the set of data provided by Ramón and fed the model with half of the files to be able to use the other half to test the effectiveness of it. It is not yet optimized to be able to use GPUs due to the graphics card of my laptop, although it has an intel iris and an nvidia gt 750m, it does not detect the second one and therefore it has to use the cpu.

The fact is that for health reasons I have not yet been able to finish it, but I will do it, I write this post so that it will be updated with the passage of time. I also have to learn to use the framework better and probably make a properly configured PC.


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