This paper addresses the challenge of transitioning computer vision systems from the prototyping stage to real-world production environments. While many existing studies focus primarily on improving model accuracy, deployment-related issues are often insufficiently explored. The paper analyzes practical and engineering aspects of production-ready computer vision systems, including model optimization, deployment environments, and computational constraints. Particular attention is paid to trade-offs between accuracy, inference speed, and resource consumption. The presented evaluations are illustrative in nature and aim to reflect typical performance trends observed during deployment. The findings provide methodological insights that may assist practitioners and engineers involved in deploying and maintaining computer vision systems.
| Mualliflar | Makharov, Kodirbek |
|---|---|
| Jurnal | Techscience.uz - техника фанлари долзарб масалалри |
| Nashr sanasi | 2026-01-31 |
| Jild | 4 |
| Son | 1 |
| Betlar | 4-11 |
| Til | Rus |
| DOI | 10.47390/ts-v4i1y2026n01 |
DOI: 10.47390/ts-v4i1y2026n01 · Maqolaning asl sahifasi
computer vision, prototyping, production systems, deployment, model optimization, performance evaluation, engineering constraints., компьютерное зрение, прототипирование, производственные системы, развертывание, оптимизация моделей, оценка производительности, инженерные ограничения.
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