Cignal uses its High-Performance Computing (HPC) Stack to rapidly train and evaluate advanced Automated Threat Recognition (ATR) models.
Cignal's HPC Stack is much more than just Designer and Checkpoint (if you haven't heard of these yet, check out our Designer and Checkpoint videos).
CignalRay is our patent-pending compute and render engine that generates 2D and 3D-imagery and labels for AI model training. CignalRay supports X-ray and X-ray CT images - as well as new types of imaging systems - and can be deployed on multiple nodes for flexible scaling.
Cignal Toolkit (CTK) allows for command-line operator access to our engine, while CTK Python Binding (PyCTK) does the same from Python environments. Both CTK and PyCTK enable dynamic and interactive training data exchanges for AI model developers, which is helpful when working with massive data sets.
Wondering how the Cignal HPC Stack could help you? Reach out to us at email@example.com for more information.
Research reported in this publication was supported by the Department of Homeland Security, Science and Technology Directorate under Award Number 70RSAT21T00000010. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Department of Homeland Security.