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Found 5 papers, 1 papers with code
SELF-VS: Self-supervised Encoding Learning For Video Summarization
Empirical evaluations on correlation-based metrics, such as Kendall's $\tau$ and Spearman's $\rho$ demonstrate the superiority of our approach compared to existing state-of-the-art methods in assigning relative scores to the input frames.
DISCERN: Diversity-based Selection of Centroids for k-Estimation and Rapid Non-stochastic Clustering
One of the applications of center-based clustering algorithms such as K-Means is partitioning data points into K clusters.
Towards Shape Biased Unsupervised Representation Learning for Domain Generalization
In this work, we propose a learning framework to improve the shape bias property of self-supervised methods.
Ranked #37 on
Domain Generalization
on PACS
Diminishing the Effect of Adversarial Perturbations via Refining Feature Representation
Our method can be applied to any layer of any arbitrary model without the need of any modification or additional training.
A Fuzzy-Rough based Binary Shuffled Frog Leaping Algorithm for Feature Selection
This paper presents a new feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset.
