Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications (SPIE Defense + Security 2027) (SDAIMLTT)

A SPIE conference within Defense + Commercial Sensing on generating and using synthetic data to train and evaluate AI/ML systems. It invites original contributions on synthetic data generation, simulation, domain adaptation, sensor modeling, generative models, AI/ML training data, validation. Submissions may take the form of full research papers, extended abstracts and poster presentations reporting theoretical, computational and experimental work, as well as industrial case studies and applications. The meeting brings together researchers, engineers, industry practitioners and students to exchange recent results and discuss emerging directions in the field. Accepted papers are published in the Proceedings of SPIE.