Astrocyte is an application based on artificial intelligence dedicated to training neural networks on 2D images for various applications. Through a highly flexible graphical user interface users can bring in their own image samples and train neural networks to perform classification, object detection, segmentation and noise reduction. Astrocyte allows visualizing and interpreting models for performance/accuracy as well as exporting these models to files for later use at runtime into Teledyne DALSA’s Sapera and Sherlock platforms.
Key Features
Graphical User Interface for rapid application development.
Training and deployment on user PC for full privacy (no cloud connection required).
Multiple deep learning architectures for a wide range of applications.
Continual Learning (aka Lifelong Learning) in classification for further learning at runtime.
Automatic generation of annotations via Semi-Supervised Object Detection (SSOD).
Access to hyperparameters for highly flexible training, including selection of neural network type.
Graphical visualization of training progress and model performance.
Availability of training heatmaps for model assessment and runtime heatmaps for object location.
Export of model file to interface with Sapera Processing and Sherlock for runtime inference.
Pre-trained models for reduced training effort (lower number of samples required).
Automatic generation and conditioning of training image files through live video acquisition from Teledyne and 3rd party cameras.
Astrocyte is an application based on artificial intelligence dedicated to training neural networks on 2D images for various applications. Through a highly flexible graphical user interface users can bring in their own image samples and train neural networks to perform classification, object detection, segmentation and noise reduction. Astrocyte allows visualizing and interpreting models for performance/accuracy as well as exporting these models to files for later use at runtime into Teledyne DALSA’s Sapera and Sherlock platforms.
Key Features
- Graphical User Interface for rapid application development.
- Training and deployment on user PC for full privacy (no cloud connection required).
- Multiple deep learning architectures for a wide range of applications.
- Continual Learning (aka Lifelong Learning) in classification for further learning at runtime.
- Automatic generation of annotations via Semi-Supervised Object Detection (SSOD).
- Access to hyperparameters for highly flexible training, including selection of neural network type.
- Graphical visualization of training progress and model performance.
- Availability of training heatmaps for model assessment and runtime heatmaps for object location.
- Export of model file to interface with Sapera Processing and Sherlock for runtime inference.
- Pre-trained models for reduced training effort (lower number of samples required).
- Automatic generation and conditioning of training image files through live video acquisition from Teledyne and 3rd party cameras.
