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Found 5 papers, 2 papers with code
Novel Class Discovery for Long-tailed Recognition
In this paper, we consider a more realistic setting for novel class discovery where the distributions of novel and known classes are long-tailed.
Class-relation Knowledge Distillation for Novel Class Discovery
In addition, to enable a flexible knowledge distillation scheme for each data point in novel classes, we develop a learnable weighting function for the regularization, which adaptively promotes knowledge transfer based on the semantic similarity between the novel and known classes.
Mutual Information-guided Knowledge Transfer for Novel Class Discovery
Our insight is to utilize mutual information to measure the relation between seen classes and unseen classes in a restricted label space and maximizing mutual information promotes transferring semantic knowledge.
CdtGRN: Construction of qualitative time-delayed gene regulatory networks with a deep learning method
Therefore, it is of great significance to elucidate the regulation mechanism over time points.
Visual Anomaly Detection for Images: A Survey
Visual anomaly detection is an important and challenging problem in the field of machine learning and computer vision.
