Every AI model depends on labeled data. Data annotation is the process of tagging images, text, audio, or video so that algorithms can learn from it. Without this step, machine learning systems can't ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Defining cellular and subcellular structures in images, referred to as cell segmentation, is an outstanding obstacle to scalable single-cell analysis of multiplex imaging data. While advances in ...