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When creating AI and ML models, most AI teams face an all-too-common problem of how to collect data for their models. The process is time-consuming, especially for a complex model that needs high-quality image annotation services for quality training data from large amounts of unlabeled data.
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When you’re working with computer vision algorithms, it becomes crucial to have an understanding of what images and videos are being used to train and test those algorithms. The images you use will have a significant effect on the success of your AI project. If you’re using image datasets that do not have accurate annotations, then your machine learning models will never become as robust as they could be.
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