Automatically Extracting Form Labels

In this paper, we address the problem of learning when some cases are fully labeled while other cases are only partially labeled, in the form of partial labels. Partial labels are represented as a set of possible labels for each training example, one of ...

Learning from hybrid labels is suitable for dealing with the real-world scenario, where the labels of the training dataset include fine-grained labels and coarse-grained labels. Unfortunately, obtaining fine-grained labels with strong supervision ...

• A novel setting called learning from hybrid labels is proposed.
• A method for identifying difficult-to-recognize images is designed.
• Hybrid-grained contrast regularization is drive.

An important problem in multi-label classification is to capture label patterns or underlying structures that have an impact on such patterns. One way of learning underlying structures over labels is to project both instances and labels into the same ...