How to prove your vision model works in production metrics
Most backend developers entering computer vision measure the wrong thing first: model accuracy. My position is narrower and more annoying: a computer vision system is working only when it improves a business decision at an acceptable latency and infrastructure cost. A high mAP model that creates slow, expensive, unaudited decisions is still a failed backend system. Your first metric should be decision yield, not model accuracy The post Computer Vision ROI Roadmap for Scalable Business Growth treats ROI as a planning problem; I would treat it as an instrumentation problem first, because a plan…
The skinny
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