The CVEDIA team supports maritime partners in efforts to develop sensor systems for situational awareness, COLREG compliant navigation, and autonomous launch and recovery. CVEDIA is an industry leader in the use of custom synthetic data to accelerate development of autonomous systems and intelligent sensors. 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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The maritime environment is variable and frequently dangerous. It’s critical that sensor suite performance limits are understood, and that operational procedures need to take into account degraded sensor performance in reduced visibility conditions.

Collecting sufficient data for this purpose poses several practical and financial challenges, not the least of which is ensuring the safety of the data collection operations team, and because of this, field data collection is rare.

As a result, one of our clients was faced with datasets which were strongly biased towards environmental conditions with excellent visibility, fair weather, and limited cloud cover. To help this particular client regain control over the statistical distribution of environmental conditions in their dataset, CVEDIA provided an open ocean simulator with a number of environmental parameters that could be easily controlled from the customer’s Python test case and data generation scripts.

The simulator was used to augment limited real world data for classifier training, giving the team tools to identify deficiencies in the statistical distribution of training data, and to generate new synthetic data to remedy deficiencies. It was also used to enable systems engineers to quantify degradation in sensor performance under simulated environmental conditions, enabling operating procedures to be formulated that ensured the safety of other mariners and the autonomous vessel itself in a shared water space.

As well as our expertise in imagery generation and simulation, CVEDIA also brings to the partnership a knowledge of how to tune the generation of synthetic data to compensate for limitations in real world datasets, as well as an understanding of how to draw real world conclusions from experiments run entirely or partially on synthetic data.

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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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    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 manufacturing scenarios that may be too difficult, expensive, or dangerous to explore, and simulate temperature conditions on your sensors
    • Choose from thousands of 3D models (or work with us to create your own) including infrastructure, production line parts, and humans to ensure your system behaves correctly during unexpected or edge case scenarios

Working with CVEDIA

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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.