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Found 4 papers, 3 papers with code
Supervised Knowledge May Hurt Novel Class Discovery Performance
Next, by using the proposed transfer flow, we conduct various empirical experiments with different levels of semantic similarity, yielding that supervised knowledge may hurt NCD performance.
DocLangID: Improving Few-Shot Training to Identify the Language of Historical Documents
In this work, we propose DocLangID, a transfer learning approach to identify the language of unlabeled historical documents.
A Closer Look at Novel Class Discovery from the Labeled Set
Novel class discovery (NCD) aims to infer novel categories in an unlabeled dataset leveraging prior knowledge of a labeled set comprising disjoint but related classes.
Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Data
One of the most pressing problems in the automated analysis of historical documents is the availability of annotated training data.
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