How do you ensure your computer vision data sets are diverse and high quality?
Computer vision is a branch of artificial intelligence (AI) that enables machines to see, understand, and interact with the world through images and videos. It has many applications, such as face recognition, self-driving cars, medical diagnosis, and security. However, to build accurate and reliable computer vision models, you need diverse and high-quality data sets that reflect the real-world scenarios and variations that your models will encounter. In this article, you will learn how to ensure your computer vision data sets are diverse and high-quality, and what tools and techniques you can use to achieve this goal.
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Muhammad Rizwan MunawarComputer Vision, Growth @ ultralytics | Open Source Contributor | YOLOv8 ?? | Vision Language Models
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Leonard Rodman, M.Sc. PMP? CSM? CSPO?IT System Administrator | AI Implementation Analyst | Agile Project Manager | 40k followers & 11M views/14mo | ChatGPT,…
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Ritika WadhawanLead - Retail Excellence Analytics | Data Science & Business Analytics Trainer @ Great Learning