Deep Vision Data® specializes in the creation of synthetic training data for supervised and unsupervised training of machine learning systems such as deep neural networks, and also the use of digital twins as virtual ML development environments. Lack of machine learning datasets is often cited as the major development obstacle for deep learning 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 or process being studied is under development and no physical data exists, or if the items of interest are rare and underrepresented in the physical dataset. Synthetic training data also mitigates privacy concerns associated with medical data and other private information. Learn more about synthetic data at Wikipedia.
Our synthetic training data are created using a variety of proprietary methods, can be multi-class, and developed for both regression and classification problems. Data annotation is automatic, zero cost, and 100% accurate. Our machine learning datasets are provided using a database and labeling schema designed for your requirements. Contact us to discuss your particular machine learning data needs.