Every factory floor is looking to improve efficiencies - be it reducing wastage, controlling yield,
optimizing expensive tool usage or quite simply improving finished product quality. TYQ-i is
Ignitarium's Visual Deep Learning based defect detection platform that can vastly improve your Quality
Keep your factory line humming with TYQ-i.
TYQ-i is a distillation of Ignitarium's deep experience in AI-for-vision. At its core, it blends the best of classical CV techniques with sparse custom neural nets to create an efficient hybrid solution for mission-critical industrial use cases.
Advanced custom (and not pre-trained open) CNNs that can be trained for high accuracy inference with minimal data sets (often less than a few 10s)
Common Neural Network platform architecture that can detect edge, surface, color or dimensional defects
Efficient SDK to allow quick deployment of the solution in live environments, irrespective of defect class being targetted
Does not require high-end purpose-built industrial grade Machine Vision cameras. Can even work with regular webcams.
The TYQ-i framework has a native benchmarking framework that allows quick identification of bottlenecks in the pipeline - be it registration, classification, inference or sub-stages in between.
Efficient architecture that can seamlessly transfer critical functions from the Vision processing pipeline into low-cost FPGAs to achieve higher frame rates or reduce latencies.
Detection of Edge and Surface deformities in Metal washers traveling on a conveyer beltRead More
Detection of presence or absence of Nuts and Bolts on designated slots of machine parts.Read More
Color detection - including shade variations - in real time.Read More