Transfer learning is a machine learning technique where a model developed for a particular task is reused as the starting point for a model on a second task, allowing for faster training and improved performance with less data. It leverages knowledge gained from previous tasks to enhance the learning efficiency and effectiveness of new tasks, especially when data for the latter is scarce.

Transfer Learning

YOLOv4

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Introduction to Generative AI: Understanding the Basics and Key Technologies

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Integrating YOLO with Custom Datasets in C#

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Creating a Custom YOLO Model from Scratch in C#

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