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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The Multi-Instance Multi-Label Learning (MIML) is an important type of machine learning framework proposed recently for IMC. In this framework, an image is described with...
Multi-label learning is the term used to express a type of supervised learning that requires classification algorithms to learn from a set of examples; each example can belong to one or multiple labels. The learning task consists of breaking the multi-label classification problem into several single label classification problems. This learning process results in the prediction of new class labels...
Primarily, the need for automatic text categorization and medical diagnosis was the start of Multi-label classification. Multi-label classification received a great attention and used in several real world applications The demand of its applications increased to cover additional fields like functional genomics, music, biology, scene, video etc. For example, a text document may belong to many subjects...
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