License Plate Recognition
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Problem
The legacy plate pipeline was classical computer vision, and it degraded exactly where real deployments live: oblique angles, motion blur, low light, and non-standard plate formats. Accuracy in the lab did not survive the parking garage.
Approach
Replaced the classical detection and OCR stages with a deep detection-and-recognition stack, sharing a backbone with the vehicle attribute models. Throughput came from CUDA implementations of depth-wise convolution layers written for the in-house library.
Result
A 20% accuracy improvement over the legacy system in production, deployed as part of Sighthound’s commercial vehicle analytics products.