Artificial Intelligence,Neural Networks,Dataset Generation,Machine Learning
Maximum number of participating students:
AR2IL / SPAN Artificial Intelligence Workshop
Deep Neural Networks are incredibly data hungry; the high performance of these algorithms is heavily dependent upon the availability of giant training datasets. In the growing field of Deep Design and Architecture, there is a huge need for the collection/creation of comprehensive labeled datasets (in both the 2D image/plan realm as well as for 3D models).
While this workshop will be a crash course instruction in Dataset Generation, including data creation and labeling methodology and tools, we will instruct students on how to create and end-to-end machine learning pipelines. Specifically, how to formulate a desired task into a problem that is solvable with machine vision tools, how to design and generate a dataset that defines the world space for this task/problem space, and finally how one can train and evaluate and algorithm on their dataset.
With these tools, the students of this workshop will be able to participate in a very unique opportunity: they will be able to contribute as both annotators and creators to AR2IL's effort to generate a novel Floor plan dataset, called Common House. The students will be credited as contributors to the dataset, and have opportunities to continue as annotators on the dataset in the months after the workshop.