March 2024
Intermediate to advanced
176 pages
4h 9m
English
In this chapter, we will dive into using active learning techniques for computer vision tasks. Computer vision involves analyzing visual data such as images and videos to extract useful information. It relies heavily on machine learning models such as convolutional neural networks. However, these models require large labeled training sets, which can be expensive and time-consuming to obtain. Active ML provides a solution by interactively querying the user to label only the most informative examples. This chapter demonstrates how to implement uncertainty sampling for diverse computer vision tasks. By the end, you will have the tools to efficiently train computer vision models with optimized labeling ...
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