A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
Robust Semi-supervised Learning for Biometrics
[chapter]
2010
Lecture Notes in Computer Science
Preserved Fulltext
To deal with the problem of sensitivity to noise in semi-supervised learning for biometrics, this paper proposes a robust Gaussian-Laplacian Regularized (GLR) framework based on maximum correntropy criterion ...
Experimental results show that the proposed GRL-MCC can effectively improve the semi-supervised learning performance and is robust to mislabeling noise and occlusion as compared with GLR. ...
Experimental results illustrate that GLR-MCC is robust against training noise for both images and labels.
Conclusion In this paper, we propose a novel robust GLR-MCC framework based on MCC. ...
doi:10.1007/978-3-642-15621-2_51
fatcat:jmzg7wbctrfcncm2u24hh4cqmu
Robust Variational Autoencoder
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We demonstrate the performance of our β-divergence based autoencoder for a range of image datasets, showing improved robustness to outliers both qualitatively and quantitatively. ...
Machine learning methods often need a large amount of labeled training data. ...
Conclusion and Discussion The presence of outliers in the form of noise, mislabeled data, and anomalies can impact the performance of machine learning models for labeling and anomaly detection tasks. ...
arXiv:1905.09961v2
fatcat:wsiny2pjqndpva6zpxtvhexbte
From Photo Streams to Evolving Situations
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
To overcome the noisy data which degrades graph quality, leading to poor recognition results, we take advantage of two kinds of noise-robust norms which can eliminate the adverse effects of outliers in ...
To extend the method for unknown situations, we introduce a soft label method which enables the traditional semi-supervised learning framework to accurately predict predefined labels as well as effectively ...
Noise Robust Semi-Supervised Learning Methods for Unknown Labels Traditional methods such as (1) are built on 2 -norm of graph embedding. ...
arXiv:1702.05878v1
fatcat:ihp4ifghzfbkhg4bvokbboytfm
l2, 1 Regularized correntropy for robust feature selection
2012
2012 IEEE Conference on Computer Vision and Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
In this paper, we study the problem of robust feature extraction based on 2,1 regularized correntropy in both theoretical and algorithmic manner. ...
Extensive experiments show that our method can select robust and sparse features, and outperforms several state-of-the-art subspace methods on largescale and open face recognition datasets. ...
Since discriminative LPP is based on a local structure which depends on label information, it is sensitive to mislabeling noise. ...
doi:10.1109/cvpr.2012.6247966
dblp:conf/cvpr/HeTWZ12
fatcat:b2cafx7n7ngndnie4g4drfg7ue
Learning Hybrid Representation by Robust Dictionary Learning in Factorized Compressed Space
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Specifically, J-RFDL performs the robust representation by DL in a factorized compressed space to eliminate the negative effects of noise and outliers on the results, which can also make the DL process ...
The setting of J-RFDL aims at improving the data representations by enhancing the robustness to outliers and noise in data, encoding the reconstruction error more accurately and obtaining hybrid salient ...
ACKNOWLEDGMENT The authors would like to express sincere thanks to reviewers for their insightful comments, making our manuscript a higher standard. ...
arXiv:1912.11785v1
fatcat:ibteex7jqfao3e6kejsdna6kzq
Semantic clusters based manifold ranking for image retrieval
2011
2011 18th IEEE International Conference on Image Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Specifically, we apply the SVM-based relevance feedback technique to create semantic clusters for computing the reliability score of each database image. ...
Our system ensures to propagate the labels in the relevance vector to the images with high reliability scores and discriminately spread the ranking scores of positive and negative images via the weighted ...
This noise resilience feature mainly results from the robust, meaningful SCs and their reliable backbone images learned in the training process. ...
doi:10.1109/icip.2011.6116133
dblp:conf/icip/ChangQ11
fatcat:bfenevvchrcevhlanmxzhwocle
A Regularized Correntropy Framework for Robust Pattern Recognition
2011
Neural Computation
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Then an l 1 regularization scheme is imposed on the correntropy to learn robust and sparse representations. ...
Second, we develop a new correntropy-based classifier based on the learned regularization scheme for robust object recognition. ...
Acknowledgments Thanks to Christian Ocier for proofreading this manuscript. We also greatly thank the associate editor and the reviewers for their valuable comments and advice. ...
doi:10.1162/neco_a_00155
fatcat:pdsqxtalejd25jm6b3irl4a2ja
MembershipMap: data transformation cased on membership aggregation
2004
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Since sub-concept labels are prone to uncertainty inherent in the original data and in the initial extraction process, a combination of labeling schemes that are based on different measures of uncertainty ...
We show that the MembershipMap can be used as a flexible pre-processing tool to support such tasks as: sampling, data cleaning, and outlier detection. ...
5)
Identifying Noise Points and Outliers Noise and outlier detection is a challenging problem. ...
doi:10.1109/icpr.2004.1334261
dblp:conf/icpr/Frigui04
fatcat:ian4ohianbadnbz3vymptcnxvm
Maximum Correntropy Criterion for Robust Face Recognition
2011
IEEE Transactions on Pattern Analysis and Machine Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
In this paper, we present a sparse correntropy framework for computing robust sparse representations of face images for recognition. ...
Compared with the state-of-the-art l 1 norm-based sparse representation classifier (SRC), which assumes that noise also has a sparse representation, our sparse algorithm is developed based on the maximum ...
ACKNOWLEDGMENTS The authors would like to greatly thank the associate editor and the reviewers for their valuable comments and advice. ...
doi:10.1109/tpami.2010.220
pmid:21135440
fatcat:leuk4exutfdx5kns3uizvjs44e
Density-based clustering of static and dynamic functional MRI connectivity features obtained from subjects with cognitive impairment
2020
Brain Informatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
To assess the robustness of clustering to noise/outliers, we propose a novel method called recursive-clustering using additive-noise (R-CLAN). ...
Results demonstrated that both clustering algorithms were effective, although OPTICS with dynamic connectivity features outperformed in terms of cluster purity (95.46%) and robustness to noise/outliers ...
ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association ...
doi:10.1186/s40708-020-00120-2
pmid:33242116
fatcat:ciw3vscdjzf7jflpm2r4snn54q
Deep Classifiers from Image Tags in the Wild
2015
Proceedings of the 2015 Workshop on Community-Organized Multimodal Mining: Opportunities for Novel Solutions - MMCommons'15
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
We introduce a large-scale robust classification algorithm, in order to handle the inherent noise in these tags, and a calibration procedure to better predict objective annotations. ...
This paper proposes direct learning of image classification from image tags in the wild, without filtering. Each wild tag is supplied by the user who shared the image online. ...
Since tag noise is different for different tags, the tag outlier probabilities are learned simultaneously with the classifier weights. ...
doi:10.1145/2814815.2814821
dblp:conf/mm/IzadiniaRFHH15
fatcat:hs5ouvy5hvgsnkhz3ftyqa4uzq
Active Concept Learning in Image Databases
2005
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Experimental results on Corel database show the efficacy of our active concept learning approach and the improvement in retrieval performance by concept transduction. ...
To achieve concept learning, we a) propose a new user directed semi-supervised expectation-maximization algorithm for mixture parameter estimation, and b) develop a novel model selection method based on ...
the noise. 2) Real Data: We implement our concept learning approach on this database with , and . ...
doi:10.1109/tsmcb.2005.846653
pmid:15971914
fatcat:prrpcpeqh5gbtfqpeecrsyjyti
Automatic Image Annotation using Possibilistic Clustering Algorithm
2019
International Journal of Fuzzy Logic and Intelligent Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Besides, the unsupervised learning task exploits the robustness to noise of a possibilistic clustering algorithm, and generates membership degrees that represent the typicality of image regions with respect ...
distribution of textual keywords and images. ...
Acknowledgements The authors are grateful for the support by the Research Center of the College of Computer and Information Sciences, King Saud University. ...
doi:10.5391/ijfis.2019.19.4.250
fatcat:nli6zyseyjb6ro53pppq4ryynu
Guide-Wire Extraction through Perceptual Organization of Local Segments in Fluoroscopic Images
[chapter]
2010
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2012; you can also visit the original URL.
The file type is application/pdf.
Komodakis for providing the clustering method. ...
In cardiac angioplasty, the problem is particularly challenging due to the following reasons: (i) low signal to noise ratio, (ii) the use of 2D images that accumulate information from the whole volume, ...
Experimental Validation Experiments were carried out on a database of 15 sequences of 10 images 1000x1000 acquired during interventions on 13 patients with a frame rate of 15 images per second, where clinical ...
doi:10.1007/978-3-642-15711-0_55
fatcat:fj7lxtzoavay3jzt3yva3jl3qm
High-accuracy classification of attention deficit hyperactivity disorder with l2,1-norm linear discriminant analysis and binary hypothesis testing
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The FCs of test data (without seeing its label) are used for training and thus affect the subspace learning of training data under binary hypotheses. ...
., insufficient data and noise disturbance. ...
Meanwhile, an l 2,1 -norm LDA model is employed for the robust feature learning to alleviate noise disturbance. ...
doi:10.1109/access.2020.2982401
fatcat:gnbejssuzrbnfpgkn7j3pglvcq
« Previous
Showing results 1 — 15 out of 7,881 results