Synthetic TALAN

Synthetic TALAN capabilities

• Planning

  Planning and setting goals

  Defining data requirements:

  We help you clearly define the task-based data requirements that your machine-learning models need to solve. This allows you to collect and process data in a way that maximizes the performance of your model.

  Identifying specific data attributes:

  Our experts identify the key data attributes that are necessary to achieve high accuracy and efficiency in your machine-learning model. This helps avoid redundant or irrelevant data, which increases the quality of your analysis and forecasting.

• Models

  Creation of basic models and scenarios

  Development of three-dimensional (3D) models and scenes

  Our team is capable of creating detailed and realistic 3D models of objects, characters, and environments. This allows us to generate high-quality data for your project, which will form the basis for further modeling and analysis.

  Programming of physical and visual properties of scenes

  Our technicians can program various physical and visual properties of scenes to reflect different real-world conditions such as lighting, weather conditions, and more. This allows you to learn and test your models in different scenarios to ensure their adaptability and effectiveness in different environments.

• Parameterization

  Parameterization and automation

  Setting data generation parameters

  We provide the ability to customize the data generation parameters to simulate different conditions such as lighting, weather conditions, and other variables. This allows you to get a variety of data to test and analyze your model under different conditions, making it more adaptable and reliable.

  Automation of the data creation process

  Our system automates the creation process to quickly and efficiently create large volumes of data. This allows you to quickly get enough data to train and test your model, which speeds up the development process and provides more accurate results.

• Generation

  Data generation

  Use of specialized tools

  We use advanced specialized tools and software to generate synthetic data. This allows us to create datasets that meet your needs and can be used to train and test your models.

  Application of virtualization and rendering methods

  Our team uses advanced virtualization and rendering techniques to create realistic and diverse images and scenarios. This allows us to generate virtual environments that can be used to generate data representing different conditions and situations for your research and development.

• Labeling

  Marking

  Automatic and manual addition of labels

  We provide both automatic and manual tagging of generated data. This means we can use machine learning algorithms to automatically label data where possible and efficiently. In cases where higher accuracy or more complex recognition is required, our experts can manually add labels to the data, ensuring reliable and accurate results.

• Validation

  Validation and testing

  Checking the quality of synthetic data

  We check the quality of synthetic data by testing it on machine learning models. This helps determine how well the synthetic data reflects real-world conditions and helps prepare the model for real-world application.

  Evaluation of data efficiency and adjustment of parameters

  We evaluate data performance in conditions that are as close to real as possible and adjust data generation parameters if necessary. This allows us to improve the quality of synthetic data and provide optimal conditions for training and testing your machine-learning models.

• Iteration

  Iteration and scaling

  Repeating the process taking into account feedback

  We iterate the process, taking into account the feedback received to improve the quality of the data. This allows us to continuously improve our data and label generation methods to ensure the highest quality for your needs.

  Process scaling

  Our system is ready for process scaling to produce large amounts of data for model training and testing. We can adapt our resources and processes to your workload, ensuring that the data you need for your project is generated quickly and efficiently.