How Many Images Do I Need to Train a Computer Vision Model? | Best Practices in 2023 скачать в хорошем качестве

How Many Images Do I Need to Train a Computer Vision Model? | Best Practices in 2023

In this comprehensive guide, the co-founder and CEO of Abud AI, delves into creating a high-quality computer vision dataset. The tutorial focuses on best practices for dataset creation, including bounding box precision, class accuracy, and the number of images for tasks like object detection, image classification, and segmentation. 🚀 Sign up now for free and explore more on Abud AI! #ComputerVision, #AI, #MachineLearning, #DataScience, #ObjectDetection, #ImageClassification, #TechTutorial Chapters: 00:05: Introduction by Rama, CEO of Abud AI 00:08: Overview of Creating Computer Vision Datasets 00:39: Principles for Dataset Creation in AI Subfields 01:06: Determining the Number of Images Needed 01:39: Exploring Examples and Use Cases 07:03: Importance of Object Classes in Datasets 09:32: Blood Cell Detection Dataset Example 11:07: Counting Oranges: A Case Study 12:20: Supermarket Shelf Product Detection 13:48: Self-Driving Cars: A Comprehensive Example 15:14: Importance of Quality Labeling in Datasets 18:02: Using Auto-Labeling to Enhance Dataset Creation 20:29: Demonstration: Effective Model with Limited Images 23:06: Final Remarks and Best Practices Summary Links and Resources: 🥳 [Sign up for free at Abud AI](https://abud.ai/ref/yt:DOM2TxT6JIc/home) 👋🏻 [Join our Discord server](  / discord  ) ✅ [Join our WhatsApp group](https://chat.whatsapp.com/CzlqpwU9rID...) 🤓 [Read our blog](https://blog.abud.ai) 📚 [Explore Abud AI official documentation](https://docs.abud.ai/deployment#use-y...) ⚡️ [Clone the Easy YOLOv7 repo](https://github.com/abud-ai/easy-yolov7) Stay tuned for more insightful content on AI and computer vision. Subscribe, like, and share if you found this video helpful. Join our community for personalized assistance!