Cited By
View all- Horikawa SNemoto CTajima KMatsubara MMorishima A(2024)An Adaptive Feature Selection Method for Learning-to-Enumerate ProblemAdvances in Information Retrieval10.1007/978-3-031-56063-7_8(122-136)Online publication date: 23-Mar-2024
Zero-shot Learning (ZSL), which aims to predict for those classes that have never appeared in the training data, has arisen hot research interests. The key of implementing ZSL is to leverage the prior knowledge of classes which builds the semantic ...
Given the descriptions of classes, Zero-Shot Learning (ZSL) aims to recognize unseen samples by learning a projection between the visual features of samples and the semantic descriptions (prototypes) of classes from seen data. However, ...
Zero-shot learning (ZSL) aims to recognize novel classes that have no labeled samples during the training phase, which leads to the domain shift problem. In reality, there exists a large number of compounded unlabeled samples. Therefore, it is ...
Association for Computing Machinery
New York, NY, United States
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in