Discover our range of in-depth blog articles concerning the topic of image annotation. Enhance your knowledge of this field, as well as learn how you can make the most of the SentiSight.ai platform’s image annotation tools.
Image annotation is a process of classifying images and creating labels to describe objects within them. It is a crucial stepping stone in a supervised machine learning project because the quality of the initial data determines the quality of the final model. A mislabeled image could lead to the model getting trained incorrectly, consequently producing undesirable results. To develop a neural network model well, data scientists are collecting vast amounts of data that contains hundreds of images. Therefore, labeling all of them correctly is a tedious, resource-heavy and lengthy process. The more people are working on the same project annotating, the more confusing it can get. Images can get duplicated, mislabeled or not labeled at all. Therefore, having a good management system is a must. To make the image annotation process more efficient programmers have developed numerous data labeling tools that allow for quicker and more precise annotation. One of these powerful tools, called SentiSight.ai is being offered by us.
Today we are releasing a new version of our platform and we have decided to start our blog to keep you updated about the progress in our development and other related news. The most significant update of this new version is AI-assisted labeling. Some AI-assisted labeling functionalities, such as smart labeling tool, have already been part of SentiSight.ai platform, but now we are bringing those to a whole new level.