===== Projects =====

Hereby, you can find projects of astronomy where we are applying Artificial Intelligence (AI).

Contributions are very welcome, please read our [[:contribution:guidelines|contribution guidelines]] to get started.

==== Open Cluster Characterization ====

The characterization and understanding of Open Clusters (OCs) allow us to understand better properties and mechanisms about the Universe such as stellar formation and the regions where these events occur. They also provide information about stellar processes and the evolution of the galactic disk.

[[https://github.com/AIAstronomy/open-cluster-characterization|https://github.com/AIAstronomy/open-cluster-characterization]]

==== Twin Galaxies ====

Detect similarities between galaxies. We employ different approach, for instance, we, first, classify the galaxies by their morphology, and then based on a Convolutional Neural Network (CNN), compares the feature vectors of the galaxies and from those vectors, we calculate the Euclidean distance establishing a ranking that will indicate the twin galaxies. One of the challenges is to find a balance between the complexity of the CNN and the hardware so that it can finish the training of the models. We train and test the models using SDSS images for objects in the CALIFA SURVEY.

[[https://github.com/AIAstronomy/twin-galaxies|https://github.com/AIAstronomy/twin-galaxies]]

==== Cosmic evolution in galaxies with active nucleus ====

Reply the Sequencer of Dayla Baron by applying planning techniques, distance metrics and expansion trees to find a sequence in more than 2000 galaxies with active nucleus.

[[https://github.com/AIAstronomy/cosmic-evolution|https://github.com/AIAstronomy/cosmic-evolution]]

==== Brown dwarfs  ====

[[https://github.com/AIAstronomy/brown-dwarfs|https://github.com/AIAstronomy/brown-dwarfs]]

==== Detect Exoplanets ====

[[https://github.com/AIAstronomy/detect-exoplanets|https://github.com/AIAstronomy/detect-exoplanets]]

==== Cloud Pattern Detections ====

[[https://github.com/AIAstronomy/cloud-patterns-detection|https://github.com/AIAstronomy/cloud-patterns-detection]]

===== Other projects =====

* [[https://arxiv.org/pdf/1911.01099.pdf|Improved detection of farside solar active regions using deep learning]]. Employ U-net architecture.