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@AircraftVerse: Empowering Aircraft Designers with a Vast Dataset of Aerial Vehicle Designs

Researchers at @SRI International, @Southwest Research Institute, @Vanderbilt University, @Purdue University, and @Carnegie Mellon University have collaborated to create an extensive dataset comprising 27,714 aircraft designs of varying complexities. This groundbreaking dataset, showcased in a pre-published paper on @arXiv, holds tremendous potential in training machine learning algorithms to provide valuable assistance to aerial vehicle designers.


The dataset is freely accessible to the public under the Creative Commons Attribution-ShareAlike (CC BY-SA) license, enabling future extensions and adaptations. To ensure its long-term availability and maintenance, the dataset is hosted at https://zenodo.org/record/6525446 and will be overseen by SRI International.


For more information, please refer to the pre-published paper on arXiv: https://arxiv.org/abs/2306.05562


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