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Jetraw AI — Custom solution for synthetic data generation based on sensor model

Generate data that mirrors natural pixel distributions
Produce multiple image-label pairs from a single dataset
Simulate sensor performance across diverse scenarios
part of research groups
meet jetraw ai

Unlike traditional data augmentation methods, Jetraw AI utilizes advanced sensor models to replicate original pixel distributions, ensuring physically accurate and high-quality outputs.

Effortlessly enrich datasets to mitigate data scarcity
Reduce costs associated with data acquisition and manual labeling
enhance model accuracy, normalization, and robustness across various settings
easy to use

Augment your dataset and enhance model performance in 3 simple steps

1
Start with a small, high-quality dataset
2
Adjust parameters to simulate various optical settings and conditions (e.g., illumination, camera quality, motion blur)m
3
Automatically generate synthetic images representing desired scenarios and apply them to your model for training
partnerships

We contribute to image standards shaping the future of data-centric AI

World Health Organization and the International Telecommunication Union
QUAREP-LiMi —Biomedical image quality standard
Croissant ML DB format with Google, NASA, Harvard, and others
FAQ

Things to know about Jetraw AI

How does Jetraw AI improve my model?

Jetraw AI enhances your model’s performance by making it more resilient to natural variations, such as changes in illumination, increased noise, and motion blur. By exposing your model to data that accurately simulates these real-world fluctuations, Jetraw AI helps your model better handle diverse and challenging conditions, ultimately improving its robustness and accuracy.

Can Jetraw AI enhance the quality of my data?

Yes, you can easily enrich your dataset with high-quality data, without the need for expensive acquisitions or manual labeling.

How does Jetraw AI differ from other synthetic data generation or augmentation tools? Why choose it over open-source alternatives?

Unlike generative models, Jetraw AI uses physics-based principles instead of machine learning to create new data samples. This method produces data that accurately reflects real-world conditions without the need for extensive training. While traditional augmentation tools manipulate existing datasets, Jetraw AI begins with a small, high-quality dataset and generates data with varying physical properties—such as illumination, noise, and motion blur—while preserving the pixel distribution of real acquisitions. The result is data that is both diverse and highly realistic.

Is Jetraw AI open-source or commercial? How can I begin using it?

Jetraw AI is a commercial solution that you can implement on CPU for automatic data generation and continuous model training. To get started, simply reach out to us. We’ll discuss your needs and requirements, provide an estimate, and if we agree to proceed, we’ll build a custom solution tailored to your specifications, which you can then integrate into your system.

Is Jetraw AI based on classical machine learning models or deep learning techniques?

No, Jetraw AI does not rely on classical machine learning models or deep learning techniques. Instead, it uses physics-based principles to generate data. This method allows Jetraw AI to create highly realistic data that accurately represents real-world conditions, without the need for traditional machine learning or deep learning models.

Is Jetraw AI compatible with CPU and GPU?

Currently, it is available off-the-shelf for CPU use; GPU support can be provided upon request.

Can I integrate Jetraw AI into my training pipeline?

Yes, Jetraw AI can be seamlessly integrated into your training pipeline. It’s designed to be compatible with existing workflows, allowing you to easily incorporate the high-quality, physics-based data generated by Jetraw AI into your model training process. This integration enhances the robustness and accuracy of your models by providing realistic and diverse data.

Is on-the-fly image generation possible with Jetraw AI?

Yes, whenever a real image is loaded, a synthetic one is automatically generated with random parameters.

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