14.2.2.3 One Class Clustering, One Class Classification

He, C.[Chao], Girolami, M.A.[Mark A.], Ross, G.[Gary],
Employing optimized combinations of one-class classifiers for automated currency validation,
PR(37), No. 6, June 2004, pp. 1085-1096.
Elsevier DOI 0405
BibRef

Wang, D., Yeung, D.S.[Daniel S.], Tsang, E.C.C.[Eric C.C.],
Structured One-Class Classification,
SMC-B(36), No. 6, December 2006, pp. 1283-1295.
IEEE DOI 0701
BibRef

Angiulli, F.[Fabrizio],
Prototype-Based Domain Description for One-Class Classification,
PAMI(34), No. 6, June 2012, pp. 1131-1144.
IEEE DOI 1205
PDD is a nearest-neighbor classifier. BibRef

Kwak, N.[Nojun], Oh, J.Y.[Ji-Yong],
Feature extraction for one-class classification problems: Enhancements to biased discriminant analysis,
PR(42), No. 1, January 2009, pp. 17-26.
Elsevier DOI 0809
Classification; One-class; One-against-rest; BDA BibRef

Oh, J.Y.[Ji-Yong], Kwak, N.[Nojun],
Generalized mean for robust principal component analysis,
PR(54), No. 1, 2016, pp. 116-127.
Elsevier DOI 1603
Generalized mean BibRef

Oh, J.H.[Jae Hyun], Kwak, N.[Nojun],
Generalization of linear discriminant analysis using -norm,
PRL(34), No. 6, 15 April 2013, pp. 679-685.
Elsevier DOI 1303
LDA; Norm; Outlier; LDA- L p BibRef

Oh, J.Y.[Ji-Yong], Kwak, N.[Nojun], Lee, M.[Minsik], Choi, C.H.[Chong-Ho],
Generalized Mean For Feature Extraction in One-Class Classification Problems,
PR(46), No. 12, 2013, pp. 3328-3340.
Elsevier DOI 1307
Generalized mean
See also Feature Extraction for Classification Problems and Its Application to Face Recognition. BibRef

Mack, B.[Benjamin], Roscher, R.[Ribana], Waske, B.[Björn],
Can I Trust My One-Class Classification?,
RS(6), No. 9, 2014, pp. 8779-8802.
DOI Link 1410
BibRef

Krawczyk, B.[Bartosz], Wozniak, M.[Michal], Herrera, F.[Francisco],
On the usefulness of one-class classifier ensembles for decomposition of multi-class problems,
PR(48), No. 12, 2015, pp. 3969-3982.
Elsevier DOI 1509
One-class classification BibRef

Krell, M.M.[Mario Michael], Wöhrle, H.[Hendrik],
New one-class classifiers based on the origin separation approach,
PRL(53), No. 1, 2015, pp. 93-99.
Elsevier DOI 1502
Origin separation approach BibRef

Liu, J.C.[Jia-Chen], Miao, Q.G.[Qi-Guang], Sun, Y.[Yanan], Song, J.F.[Jian-Feng], Quan, Y.[Yining],
Fast structural ensemble for One-Class Classification,
PRL(80), No. 1, 2016, pp. 179-187.
Elsevier DOI 1609
One-class classifier BibRef

Ao, Z.[Zurui], Su, Y.J.[Yan-Jun], Li, W.K.[Wen-Kai], Guo, Q.H.[Qing-Hua], Zhang, J.[Jing],
One-Class Classification of Airborne LiDAR Data in Urban Areas Using a Presence and Background Learning Algorithm,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Son, Y.[Youngdoo], Lee, S.[Sujee], Park, S.[Saerom], Lee, J.W.[Jae-Wook],
Learning representative exemplars using one-class Gaussian process regression,
PR(74), No. 1, 2018, pp. 185-197.
Elsevier DOI 1711
Representative, exemplars BibRef

Bicego, M.[Manuele], Figueiredo, M.A.T.[Mário A.T.],
Clustering via binary embedding,
PR(83), 2018, pp. 52-63.
Elsevier DOI 1808
Clustering, Binary embedding, Finite mixture models, Biclustering, One-class classification BibRef

Yu, J.[Jaehong], Kang, S.[Seokho],
Clustering-based proxy measure for optimizing one-class classifiers,
PRL(117), 2019, pp. 37-44.
Elsevier DOI 1901
One-class classification, One-class classifier, Hyperparameter optimization, Proxy measure, Model validation, Pseudo non-target class BibRef

Perera, P., Patel, V.M.,
Learning Deep Features for One-Class Classification,
IP(28), No. 11, November 2019, pp. 5450-5463.
IEEE DOI 1909
Feature extraction, Training, Task analysis, Training data, Anomaly detection, Authentication, Deep learning, deep learning BibRef

Sansone, E.[Emanuele], de Natale, F.G.B.[Francesco G. B.], Zhou, Z.H.[Zhi-Hua],
Efficient Training for Positive Unlabeled Learning,
PAMI(41), No. 11, November 2019, pp. 2584-2598.
IEEE DOI 1910
Learn a classifier for a class of interest from an unlabeled data set. Semisupervised learning, Training, Task analysis, Kernel, Optimization, Statistical learning, Scalability, Machine learning, kernel methods BibRef

Kumar, N., Awate, S.P.,
Semi-Supervised Robust Mixture Models in RKHS for Abnormality Detection in Medical Images,
IP(29), 2020, pp. 4772-4787.
IEEE DOI 2003
Robustness, Training, Semisupervised learning, Kernel, Data models, Image segmentation, Biomedical imaging, Abnormality detection, semi-supervised learning BibRef

Kumar, N., Chandran, S., Rajwade, A.V., Awate, S.P.,
Semi-Supervised Robust One-Class Classification in RKHS for Abnormality Detection in Medical Images,
ICIP19(544-548)
IEEE DOI 1910
Abnormality detection, one-class classification, kernel, robust modeling, semi-supervised learning. BibRef

Zhao, L.[Liya], Waldner, F.[François], Scarth, P.[Peter], Mack, B.[Benjamin], Hochman, Z.[Zvi],
Combining Fractional Cover Images with One-Class Classifiers Enables Near Real-Time Monitoring of Fallows in the Northern Grains Region of Australia,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Mauceri, S.[Stefano], Sweeney, J.[James], McDermott, J.[James],
Dissimilarity-based representations for one-class classification on time series,
PR(100), 2020, pp. 107122.
Elsevier DOI 2005
Dissimilarity-based representations, One-class classification, Time series BibRef

Xing, H.J.[Hong-Jie], Liu, Y.J.[Ya-Jie], He, Z.C.[Zi-Chuan],
Robust sparse coding for one-class classification based on correntropy and logarithmic penalty function,
PR(111), 2021, pp. 107685.
Elsevier DOI 2012
Sparse coding, One-class classification, Logarithmic penalty function, Correntropy, One-class support vector machine BibRef

La Grassa, R.[Riccardo], Gallo, I.[Ignazio], Landro, N.[Nicola],
OCmst: One-class novelty detection using convolutional neural network and minimum spanning trees,
PRL(155), 2022, pp. 114-120.
Elsevier DOI 2203
Novelty detection, Convolutional neural network, Minimum spanning tree, One-class BibRef

Noronha, M.D.M.[Marta D.M.], Henriques, R.[Rui], Madeira, S.C.[Sara C.], Zárate, L.E.[Luis E.],
Impact of metrics on biclustering solution and quality: A review,
PR(127), 2022, pp. 108612.
Elsevier DOI 2205
Merit functions, Biclustering evaluation, Biclustering validation, Bicluster discovery, Systematic review BibRef

Zaheer, M.Z.[Muhammad Zaigham], Lee, J.H.[Jin-Ha], Mahmood, A.[Arif], Astrid, M.[Marcella], Lee, S.I.[Seung-Ik],
Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies,
IP(31), 2022, pp. 5963-5975.
IEEE DOI 2209
Training, Image reconstruction, Anomaly detection, Generators, Feature extraction, Detectors, Training data, Novelty detection, stabilizing adversarial models BibRef

Lo, S.Y.[Shao-Yuan], Oza, P.[Poojan], Patel, V.M.[Vishal M.],
Adversarially Robust One-Class Novelty Detection,
PAMI(45), No. 4, April 2023, pp. 4167-4179.
IEEE DOI 2303
Anomaly detection, Detectors, Principal component analysis, Robustness, Task analysis, Perturbation methods, one-class classification BibRef

Arashloo, S.R.[Shervin Rahimzadeh],
One-Class Classification Using lp-Norm Multiple Kernel Fisher Null Approach,
IP(32), 2023, pp. 1843-1856.
IEEE DOI 2303
Kernel, Support vector machines, Task analysis, Training, Optimization, Search problems, lp-norm regularisation BibRef

Sun, W.J.[Wen-Ju], Li, Q.Y.[Qing-Yong], Zhang, J.[Jing], Wang, D.Y.[Dan-Yu], Wang, W.[Wen], Geng, Y.L.[Yang-Liao],
Exemplar-Free Class Incremental Learning via Discriminative and Comparable Parallel One-Class Classifiers,
PR(140), 2023, pp. 109561.
Elsevier DOI 2305
Incremental learning, Continual learning, Lifelong learning, One-class learning, Image classification BibRef

Chiou, C.Y.[Chien-Yu], Lee, K.T.[Kuang-Ting], Huang, C.R.[Chun-Rong], Chung, P.C.[Pau-Choo],
ADMM-SRNet: Alternating Direction Method of Multipliers Based Sparse Representation Network for One-Class Classification,
IP(32), 2023, pp. 2843-2856.
IEEE DOI 2306
Training, Feature extraction, Testing, Dictionaries, Computational modeling, Image reconstruction, Deep learning, sparse representation BibRef

Lee, H.H.[Hae-Hwan], Park, S.[Seunghwan], Im, J.[Jongho],
Resampling approach for one-Class classification,
PR(143), 2023, pp. 109731.
Elsevier DOI 2310
One-class classification, Data-driven approach, Oversampling, Calibration BibRef

Xing, H.J.[Hong-Jie], Liu, W.T.[Wei-Tao], Wang, X.Z.[Xi-Zhao],
Bounded exponential loss function based AdaBoost ensemble of OCSVMs,
PR(148), 2024, pp. 110191.
Elsevier DOI 2402
One-class classification, AdaBoost, Exponential loss function, One-class support vector machine, Outliers BibRef

Abady, L.[Lydia], Dimitri, G.M.[Giovanna Maria], Barni, M.[Mauro],
A One-Class Classifier for the Detection of GAN Manipulated Multi-Spectral Satellite Images,
RS(16), No. 5, 2024, pp. 781.
DOI Link 2403
BibRef

Tian, C.R.[Chong-Rui], Zhang, F.B.[Feng-Bin], Wang, R.D.[Rui-Dong],
Adversarial regularized attributed network embedding for graph anomaly detection,
PRL(183), 2024, pp. 111-116.
Elsevier DOI 2406
Attributed network embedding, Adversarial regularization, Neural network, One-class classification BibRef

Zhang, Z.L.[Zi-Long], Zhao, Z.B.[Zhi-Bin], Zhang, X.[Xingwu], Chen, X.F.[Xue-Feng],
DA2: Distribution-agnostic adaptive feature adaptation for one-class classification,
CVIU(251), 2025, pp. 104256.
Elsevier DOI 2501
Self-supervised learning, Non-contrastive learning, One-class classification BibRef

Liang, D.J.[Dao-Jun], Zhang, H.X.[Hai-Xia], Yuan, D.F.[Dong-Feng], Zhang, M.G.[Ming-Gao],
Multi-Head Encoding for Extreme Label Classification,
PAMI(47), No. 3, March 2025, pp. 2199-2211.
IEEE DOI 2502
Training, Encoding, Testing, Computational modeling, Magnetic heads, Tensors, Face recognition, Vocabulary, Vectors, Semantics, extreme multi-label classification BibRef

La Grassa, R.[Riccardo], Gallo, I.[Ignazio], Landro, N.[Nicola],
Dynamic Decision Boundary for One-class Classifiers applied to non-uniformly Sampled Data,
DICTA20(1-7)
IEEE DOI 2201
Machine learning algorithms, Digital images, Machine learning, Predictive models, Robustness BibRef

Pourreza, M.[Masoud], Mohammadi, B.[Bahram], Khaki, M.[Mostafa], Bouindour, S.[Samir], Snoussi, H.[Hichem], Sabokrou, M.[Mohammad],
G2D: Generate to Detect Anomaly,
WACV21(2002-2011)
IEEE DOI 2106
Training, Computational modeling, Neural networks, Generative adversarial networks, Generators BibRef

Larin, A.O.[Aleksandr O.], Seredin, O.S.[Oleg S.], Kopylov, A.V.[Andrey V.],
One-class Classification Criterion Robust to Anomalies in Training Dataset,
IMTA20(155-165).
Springer DOI 2103
BibRef

Choi, S., Chang, I., Teoh, A.B.J.,
One-class Random Maxout Probabilistic Network for Mobile Touchstroke Authentication,
ICPR18(3359-3364)
IEEE DOI 1812
Authentication, Probabilistic logic, Training, Biometrics (access control), Feature extraction, Random maxout BibRef

Kozerawski, J., Turk, M.,
CLEAR: Cumulative LEARning for One-Shot One-Class Image Recognition,
CVPR18(3446-3455)
IEEE DOI 1812
Training, Support vector machines, Training data, Task analysis, Convolutional neural networks, Benchmark testing BibRef

Mygdalis, V., Iosifidis, A., Tefas, A., Pitas, I.,
One class classification applied in facial image analysis,
ICIP16(1644-1648)
IEEE DOI 1610
Computational modeling BibRef

Aghdam, H.H.[Hamed Habibi], Heravi, E.J.[Elnaz Jahani], Puig, D.[Domenec],
A New One Class Classifier Based on Ensemble of Binary Classifiers,
CAIP15(II:242-253).
Springer DOI 1511
BibRef

Hadjadji, B.[Bilal], Chibani, Y.[Youcef], Guerbai, Y.[Yasmine],
Multiple One-Class Classifier Combination for Multi-class Classification,
ICPR14(2832-2837)
IEEE DOI 1412
Accuracy BibRef

Hadjadji, B.[Bilal], Chibani, Y.[Youcef], Nemmour, H.[Hassiba],
Fuzzy Integral Combination of One-Class Classifiers Designed for Multi-class Classification,
ICIAR14(I: 320-328).
Springer DOI 1410
BibRef

Wang, Q.H.[Qing-Hua], Lopes, L.S.[Luís Seabra], Tax, D.M.J.[David M.J.],
Visual Object Recognition Through One-Class Learning,
ICIAR04(I: 463-470).
Springer DOI 0409
BibRef

Tax, D.M.J., Muller, K.R.,
A Consistency-Based Model Selection for One-Class Classification,
ICPR04(III: 363-366).
IEEE DOI 0409

See also Component-Based Discriminative Classification for Hidden Markov Models. BibRef

Hocquet, S.[Sylvain], Ramel, J.Y.[Jean-Yves], Carbot, H.[Hubert],
Estimation of User Specific Parameters in One-class Problems,
ICPR06(IV: 449-452).
IEEE DOI 0609
BibRef

Ilonen, J., Paalanen, P., Kamarainen, J.K., Kalviainen, H.,
Gaussian mixture pdf in one-class classification: computing and utilizing confidence values,
ICPR06(II: 577-580).
IEEE DOI 0609
BibRef

Ercil, A., Buke, B.,
One class classification using implicit polynomial surface fitting,
ICPR02(II: 152-155).
IEEE DOI 0211
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
High Dimensional Data, Hyperspectral Data, Hyper-Spectral Data Classification .