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A review on semi-supervised clustering
J Cai, J Hao, H Yang, X Zhao, Y Yang - Information Sciences, 2023 - Elsevier
Abstract Semi-supervised clustering (SSC), a technique integrating semi-supervised
learning and clustering analysis, incorporates the given prior information (eg, class labels …
learning and clustering analysis, incorporates the given prior information (eg, class labels …
Object tracking: A survey
The goal of this article is to review the state-of-the-art tracking methods, classify them into
different categories, and identify new trends. Object tracking, in general, is a challenging …
different categories, and identify new trends. Object tracking, in general, is a challenging …
Guarantees for spectral clustering with fairness constraints
Given the widespread popularity of spectral clustering (SC) for partitioning graph data, we
study a version of constrained SC in which we try to incorporate the fairness notion …
study a version of constrained SC in which we try to incorporate the fairness notion …
Image retrieval: Ideas, influences, and trends of the new age
We have witnessed great interest and a wealth of promise in content-based image retrieval
as an emerging technology. While the last decade laid foundation to such promise, it also …
as an emerging technology. While the last decade laid foundation to such promise, it also …
Unsupervised hierarchical semantic segmentation with multiview cosegmentation and clustering transformers
Unsupervised semantic segmentation aims to discover grou**s within and across images
that capture object-and view-invariance of a category without external supervision. Grou** …
that capture object-and view-invariance of a category without external supervision. Grou** …
Segsort: Segmentation by discriminative sorting of segments
Almost all existing deep learning approaches for semantic segmentation tackle this task as a
pixel-wise classification problem. Yet humans understand a scene not in terms of pixels, but …
pixel-wise classification problem. Yet humans understand a scene not in terms of pixels, but …
Robust path-based spectral clustering
Spectral clustering and path-based clustering are two recently developed clustering
approaches that have delivered impressive results in a number of challenging clustering …
approaches that have delivered impressive results in a number of challenging clustering …
General heuristics for nonconvex quadratically constrained quadratic programming
We introduce the Suggest-and-Improve framework for general nonconvex quadratically
constrained quadratic programs (QCQPs). Using this framework, we generalize a number of …
constrained quadratic programs (QCQPs). Using this framework, we generalize a number of …
Nonlocal linear image regularization and supervised segmentation
A nonlocal quadratic functional of weighted differences is examined. The weights are based
on image features and represent the affinity between different pixels in the image. By …
on image features and represent the affinity between different pixels in the image. By …
Active co-analysis of a set of shapes
Unsupervised co-analysis of a set of shapes is a difficult problem since the geometry of the
shapes alone cannot always fully describe the semantics of the shape parts. In this paper …
shapes alone cannot always fully describe the semantics of the shape parts. In this paper …