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Image annotation is integral to machine learning and artificial intelligence, especially when using computer vision (CV) models. It is the process where images of a particular dataset are labeled to help train a machine learning model. Different image annotation techniques such as polygon annotations and bounding boxes can do this. The benefits and importance of
Artificial intelligence (AI) and machine learning are here to stay. They have changed the way we live and experience the world around us. These technologies throw up some amazing opportunities that can help drive the global economy. Be it music, banking, or medical care, you will find machine learning and algorithms powering the latest innovations.
Businesses are embracing Machine Learning (ML) and Artificial Intelligence (AI) for text and image annotation because of the accuracy, speed and comprehensiveness these services provide. In addition, these services eliminate the risks associated with managing data diversity, reducing bias and scaling. The annotation process begins with marking up a dataset and its characteristics with a
The data annotation market is expected to grow at 25.6% for the next five years. The adoption of AI-based services in different domains has contributed to this rise in demand. Many sectors such as healthcare, automobiles, telecom, and e-commerce among others are finding it expedient to collect datasets from different sources and label them based