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Unsupervised Manifold Learning for Video Genre Retrieval
(Springer, 2014-01-01)
This paper investigates the perspective of exploiting pairwise similarities to improve the performance of visual features for video genre retrieval. We employ manifold learning based on the reciprocal neighborhood and on ...
Unsupervised manifold learning for video genre retrieval
(2014-01-01)
This paper investigates the perspective of exploiting pairwise similarities to improve the performance of visual features for video genre retrieval. We employ manifold learning based on the reciprocal neighborhood and on ...
Unsupervised manifold learning by correlation graph and strongly connected components for image retrieval
(2014-01-28)
This paper presents a novel manifold learning approach that takes into account the intrinsic dataset geometry. The dataset structure is modeled in terms of a Correlation Graph and analyzed using Strongly Connected Components ...
A rank-based framework through manifold learning for improved clustering tasks
(2021-11-01)
The relevance of diversified data preprocessing approaches for improving clustering tasks is remarkable. Once the effectiveness is direct impacted by feature representation and similarity definition, considerable attention ...
A Study of the ISOMAP Algorithm and Its Applications in Machine Learning
(Universidade Federal de São CarlosUFSCarCâmpus São CarlosCiência da Computação - CC, 2015-12-11)
This project aims to study the foundations of nonlinear dimensionality reduction through manifold learning with the algorithm known as Isometric Feature Mapping (ISOMAP) and observe the application of the algorithm in ...
A correlation graph approach for unsupervised manifold learning in image retrieval tasks
(2016-10-05)
Effectively measuring the similarity among images is a challenging problem in image retrieval tasks due to the difficulty of considering the dataset manifold. This paper presents an unsupervised manifold learning algorithm ...
Representation Learning for Image Retrieval through 3D CNN and Manifold Ranking
(2021-01-01)
Despite of the substantial success of Convolutional Neural Networks (CNNs) on many recognition and representation tasks, such models are very reliant on huge amount of data to allow effective training. In order to improve ...
Manifold learning-based clustering approach applied to anomaly detection in surveillance videos
(2020-01-01)
The huge increase in the amount of multimedia data available and the pressing need for organizing them in different categories, especially in scenarios where there are no labels available, makes data clustering an essential ...
Manifold Learning-based Clustering Approach Applied to Anomaly Detection in Surveillance Videos
(Scitepress, 2020-01-01)
The huge increase in the amount of multimedia data available and the pressing need for organizing them in different categories, especially in scenarios where there are no labels available, makes data clustering an essential ...