Deep Vision Data specializes in the creation of synthetic training data for supervised training of machine learning systems such as deep neural networks. Lack of training data sets for neural networks is often cited as the major development obstacle for these systems, and creating and labeling sufficient data from physical testing and other non-algorithmic methods such as photography can be extremely time consuming or impossible. The problem is further compounded when the product, object or process being studied is currently under development and no physical images or data exist. Synthetic training data also mitigates privacy concerns associated with the use of medical data and other private information. Learn more about synthetic data at Wikipedia.
Our synthetic training data sets for neural networks are created using a variety of proprietary methods, can be multi-class, and developed for both regression and classification problems. The data can be used as-is or as input for a generative adversarial network (GAN). Your data sets are provided using a database and labeling schema designed for your requirements. Contact us today to discuss your particular training and validation data needs.