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Found 3 papers, 1 papers with code
Attributes Grouping and Mining Hashing for Fine-Grained Image Retrieval
To handle this limitation, we substitute convolutional descriptors for attention-guided features and propose an Attributes Grouping and Mining Hashing (AGMH), which groups and embeds the category-specific visual attributes in multiple descriptors to generate a comprehensive feature representation for efficient fine-grained image retrieval.
RRMSE Voting Regressor: A weighting function based improvement to ensemble regression
This paper describes the RRMSE (Relative Root Mean Square Error) based weights to weight the occurrences of predictive values before averaging for the ensemble voting regression.
Interpretation of multi-label classification models using shapley values
Multi-label classification is a type of classification task, it is used when there are two or more classes, and the data point we want to predict may belong to none of the classes or all of them at the same time.
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