VISION SERIES FROM PIXELS TO PRODUCTION A model that scores 99% on a benchmark doesn't matter if it chokes on a dusty lens. A camera that reads barcodes but fails when the lighting shifts costs money every minute it sits idle.

That's the reality of machine vision in production, and it's exactly the problem this series attacks. Over three books, Evan Norvell builds a complete engineering path: start with deterministic camera systems, add AI where it earns its keep, then move into multimodal reasoning that makes decisions from images, video, and language.

No hype, no benchmark chasing. Just systems that work after the demo.

Here's what each book brings, in order: 👉 Practical Vision Systems: Camera-Based Solutions for Recognition, Measurement, Inspection, and Automation. The foundation.

Build controlled imaging environments with the right optics, lighting, and exposure before touching an algorithm. Master barcode reading, OCR, measurement, and surface inspection using deterministic pipelines that are predictable and debuggable.

👉 Applied AI Vision Systems: Detection, Segmentation, Tracking, Inspection, and Intelligent Automation. The leap to deep learning, done responsibly.

Learn when AI is the right tool, how to handle occlusion and changing environments, and how to design for graceful degradation. Covers deployment, monitoring, and...