The CVEDIA team supports smart city partners in testing, training, and validating their systems. CVEDIA is an industry leader in the use of custom synthetic data to develop new sensor technology or smart cities. Our systems have been precisely built to minimize the gap between real and synthetic data for fluid algorithm training.

CVEDIA simulation tools are designed from the ground up to support and accelerate development from the earliest to the latest stages in the development process. Our SynCity simulation platform provides broadly representative data for new projects, and is used in data intensive classifier training to augment real world data, fill in gaps in coverage, and control for sampling bias. The result is rapidly produced, higher quality training sets that dramatically reduce field data collection, data storage, and labelling expenses.

Use Case

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CVEDIA is invested in using AI to create a safer planet. Through synthetic data, we work with clients to understand the risks of dangerous intersections and areas, and enable cities to create effective systems to keep their citizens safe.

By creating effective simulations for city developers, we can train machine learning systems to recognize people, vehicles, bicycles, and city infrastructure. Using this technology, developers can then gather effective data regarding traffic, accidents, volume, and safety incidents.

CVEDIA synthetic data is effective for providing a low cost means of gathering sufficient training data. Create unlimited training sets in SynCity, and employ multiple synthetic sensors to test which are most effective, where to place them, and how your algorithms recognize their input separately and collectively.

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Synthetic Datasets Train your machine learning model on validated synthetic data
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SynCity Use SynCity to develop, train, and validate your computer vision system with custom simulations
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Algorithm Training CVEDIA Algorithm Training Services
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Benefits
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    Reduce total project expense
    • SynCity reduces or eliminates the need for sensor deployment and field data
    • CVEDIA synthetic data dramatically reduces data collection and storage expenses
    • SynCity retrieves metadata and annotation from synthetic data - an expense you can absolve from your project
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    Minimize project length
    • Training autonomous applications on synthetic data dramatically reduces time requirements for gathering and organizing field data
    • Datasets can be created and exported in minutes in the browser with SynCity
    • CVEDIA uses assisted algorithm training by choosing which algorithms to apply to most quickly and completely validate your machine learning system
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    Validate your system effectively
    • Account for unmet field data scenarios that may be too difficult, expensive, or dangerous to explore, and simulate fog, sun glare, dust, sand, and water on your sensors
    • Choose from thousands of 3D models (or work with us to create your own) including city infrastructure, natural elements, and humans to ensure your system behaves correctly during unexpected or edge case scenarios

Working with CVEDIA

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Talk to a team member

CVEDIA projects are developed by an experienced in-house team led by synthetic data industry leaders Arjan Wijnveer and Rodrigo Orph. Our team has been carefully vetted for over 10 years and includes AI veterans with backgrounds in machine learning R&D and large scale deployment.

CVEDIA works iteratively on client projects until satisfactory results are met. Our team has been met with praise from previous and ongoing clients across a range of industries, and we’re happy to be backed by FLIR Systems, the world’s leading thermal sensor producer. CVEDIA works to create custom environments and tool systems for each project, with varying levels of in-house service dependent on client needs.