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Synthetic Training Data Infographic

Synthetic Training Data

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. Labeling and semantic segmentation are automatic and 100% accurate. 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.

Synthetic Training Data Mobile Infographic
Deep Vision Data - Synthetic Product Images

Synthetic Product Images

Synthetic product images are 100% virtual and can include variability in pose, lighting, material finish and many other factors. Portions of the images can be occluded to simulate handling or other situations, and the renderings can be photorealistic, grey-scale or silhouette. Need 10,000 images in a few days?
No problem!

Deep Vision Data - Hybrid Synthetic-Physical Product Images

Hybrid Synthetic-Physical Images

Need thousands of training images of your product presented in a specific physical environment, and you need them fast? Mobile devices running augmented reality (AR) apps can be utilized to quickly create hybrid images of virtual objects in physical environments. Useful for when the environment contains important class information.

Deep Vision Data - Synthetic Environment Images

Synthetic Environment Images

Synthetic environment images can be interior or exterior and are used to train systems to detect safety, compliance, stocking, manufacturing process deviations and many other functions. Scenes are database-driven to enable rapid variation of merchandising plans, factory setups, warehouse configurations and other scenarios.

Deep Vision Data - Real-Time Simulators

Real-Time Simulation

Real-time simulators utilize game engines and custom software to replicate physical products, systems and processes. They can be implemented in virtual reality (VR) environments to create fully immersive training experiences. Multiple simultaneous instances of the real-time simulation environment can be utilized to rapidly speed up the training process.

Deep Vision Data - Modeling and Simulation

Modeling and Simulation

Modeling and simulation is used to explore product life cycle, performance, etc. due to variation in component dimensions, production quality, process parameters and other real-world variances. This data can be used to create intelligent systems that guide users to design products or systems which have optimized cost, performance or weight goals.

Deep Vision Data - Design Variation

Design Variation

Computer-aided design (CAD) tools are used to algorithmically vary component dimensions or assembly parameters. The resulting data can be utilized to train intelligent production vision systems to identify manufacturing or quality issues that are too complex for traditional in-line processes. Coupled with industrial 3D scanning, machine learning creates the next evolution of part inspection.

Our Vertical Markets

Deep Vision Data is the industry leader in synthetic training data creation for a range of markets.

Deep Vision Data - Our Expertise

Our Expertise

  • Multi-disciplinary expertise in design, engineering, modeling and simulation software/app/simulator development, digital art and industrial 3D scanning.
  • Proprietary software infrastructure for data creation, labeling and warehousing
  • Ability to rapidly create product 3D models from physical samples or digital data
  • Expertise with all major computer-aided design (CAD) and digital modeling software
  • Expertise with all major modeling and simulation software systems
  • Ability to create labeled training, validation and testing data sets for neural networks

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