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Interactive Causal Correlation Space Reshape for Multi-Label Classification
Most existing multi-label classification models focus on distance metrics and feature spare strategies to extract specific features of labels. Those models use the cosine similarity to construct the label correlation matrix ...
Interactive image segmentation using label propagation through complex networks
(2019-06-01)
Interactive image segmentation is a topic of many studies in image processing. In a conventional approach, a user marks some pixels of the object(s) of interest and background, and an algorithm propagates these labels to ...
Multi-label semi-supervised classification through optimum-path forest
(Elsevier B.V., 2018-10-01)
Multi-label classification consists of assigning one or multiple classes to each sample in a given dataset. However, the project of a multi-label classifier is usually limited to a small number of supervised samples as ...
Particle Competition and Cooperation in Networks for Semi-Supervised Learning
(IEEE COMPUTER SOCLOS ALAMITOS, 2012)
Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) ...
Particle Competition and Cooperation in Networks for Semi-Supervised Learning
(Institute of Electrical and Electronics Engineers (IEEE), Computer Soc, 2012-09-01)
Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) ...
Particle Competition and Cooperation in Networks for Semi-Supervised Learning
(Institute of Electrical and Electronics Engineers (IEEE), Computer Soc, 2012-09-01)
Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) ...
A semi-supervised classification technique based on interacting forces
(ElsevierAmsterdam, 2014-03-15)
Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by ...
Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning
(2012-12-01)
Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate ...
Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning
(2012-12-01)
Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate ...
Visual active learning for labeling: A case for soundscape ecology data
(2021-07-01)
Labeling of samples is a recurrent and time-consuming task in data analysis and machine learning and yet generally overlooked in terms of visual analytics approaches to improve the process. As the number of tailored ...