Fine-grained classification is a term used in the fields of artificial intelligence, big data, smart data and digital transformation. It describes how computers or machines are enabled to recognise and assign very subtle differences between similar objects, images or data.
Instead of only making a rough distinction between "bird" and "dog", for example, Fine-Grained Classification can precisely distinguish between several similar bird species, such as a sparrow and a titmouse. This is particularly valuable when details make the difference, such as in quality assurance in a factory, where very similar screws or components need to be recognised.
Fine-grained classification is made possible by modern algorithms and large amounts of data that are increasingly able to recognise patterns and subtle differences. For example, online shops can use this technology to automatically sort similar products and give customers suitable recommendations.
Overall, Fine-Grained Classification helps companies to automate processes that previously only humans could do reliably - bringing more precision and efficiency to digital applications.
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