Technology

Classification

Is this X or Y?

Assigns an image or region to a category from a trained set. L-DNN learns each class from a small number of representative images and can add new classes in the field without cloud retraining or a GPU.

Example applications Product identification · Material & surface type recognition · Pass/fail grading · Part type sorting · Label and marking verification · Object categorization by visual property

Anomaly detection

Does this look right?

Learns what "normal" looks like from a small reference set, then flags anything that deviates, without requiring labeled examples of every possible defect or failure mode.

Example applications Surface irregularity detection · Packaging integrity verification · Seal and closure inspection· Foreign object detection · Contamination identification · Any scenario where failure modes are unpredictable or hard to pre-label

Detection

What is it and where is it?

Locates and identifies specific objects within a frame, returning bounding box coordinates alongside classification. Trains and runs fully on-device with no GPU, providing both identification and precise spatial position.

Example applications Label and text localization · Barcode and marking position detection · Object counting and tracking · Presence/absence verification · Spatial positioning for robotics · Multi-object scene parsing

See L-DNN inside your product

Our engineering team is ready to walk through how L-DNN would integrate into your specific hardware and software stack - and what it would take to get there.

Talk to our team

No sales pitch. A real technical conversation.