Deep learning Models are Hungry for the Right Data

Artificial intelligence (AI) is penetrating more and more areas, and the manufacturing industries are no exception. In today's manufacturing industry, deep learning (DL) is used in a variety of industries to perform repetitive tasks.
One of the greatest challenges in the development of neural networks is the need to develop adaptable yet robust control algorithms that can take into account all possible behaviours of the system and respond appropriately to unforeseen situations.
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Building High-Quality Models In 3 Steps

Explore our services: Efficiently leveraging data analysis, data generation, and integration tools for superior model performance.
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Data Insight

Review and analysis of existing data to provide key insights and recommendations for optimizing your dataset.
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Data Generation

Generation of synthetic data and data augmentation to create an optimal dataset based on key insights from the analysis.
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Data Import

Tools for importing data into industry-standard deep learning software.

Additional Resources

Explore Key Concepts and Benefits of Synthetic Data and corresponding Annotations.

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What is Synthetic Data?

Learn about the fundamentals of synthetic data, its generation process, and its applications in various industries.

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Why Use Synthetic Data?

Understand the benefits of synthetic data, including enhanced model training, cost efficiency, and the ability to generate rare or hard-to-capture scenarios.

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How Real is Synthetic Data?

Explore the realism and accuracy of synthetic data compared to real-world data, and how it can be tailored to match specific use cases.

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Annotations

Explore the critical role of high-quality annotations in dataset preparation. Our synthetic image data comes fully annotated, as our generation process precisely tracks and identifies every element within each image, ensuring consistent and accurate labelling.

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3D Rendering

Our 3D rendering process leverages advanced computer graphics techniques to create highly realistic and detailed synthetic images. This approach allows us to simulate a wide range of scenarios and environments.

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Generative Approaches

Our generative data creation techniques use advanced AI models to enhance realism and add details to the 3D rendered synthetic image.
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Haven’t found your use case?

If you are facing challenges with data acquisition and are considering the use of synthetic images for an application not listed here, contact us – we would be glad to work together towards a solution.
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