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Ensembles of Deep One-Class Classifiers for Multi-Class Image Classification

https://doi.org/10.2139/ssrn.4869376
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The Novelty Detection Approach for Different Degrees of Class Imbalance
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Ensemble Methods in Machine Learning
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Combining One-Class Classifiers
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Pattern Classification
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Conditional Infilling GANs for Data Augmentation in Mammogram Classification
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GANomaly: Semi-supervised Anomaly Detection via Adversarial Training
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Diffusion Models for Medical Anomaly Detection
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BlobGAN: Spatially Disentangled Scene Representations
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U-Net: Convolutional Networks for Biomedical Image Segmentation
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Generative Visual Manipulation on the Natural Image Manifold
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Combining One-Class Classifiers to Classify Missing Data
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One-Class Classification by Combining Density and Class Probability Estimation
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Face Recognition Using Eigenfaces
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A new maximal-margin spherical-structured multi-class support vector machine
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Plant leaf disease classification using EfficientNet deep learning model
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Cytological image analysis with firefly nuclei detection and hybrid one-class classification decomposition
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Multi-class classification via heterogeneous ensemble of one-class classifiers
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Clustering-based ensembles for one-class classification
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Dynamic selection and combination of one-class classifiers for multi-class classification
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An ensemble of autonomous auto-encoders for human activity recognition
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Domain described support vector classifier for multi-classification problems
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An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes
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On the usefulness of one-class classifier ensembles for decomposition of multi-class problems
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Dynamic ensemble selection for multi-class classification with one-class classifiers
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One-class classification: taxonomy of study and review of techniques
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Random Forests
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Support Vector Data Description
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On combining classifiers
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Support vector machines
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Fully convolutional networks for semantic segmentation
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Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2018.00356openalex-extracted
Adversarially Learned One-Class Classifier for Novelty Detection
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A Style-Based Generator Architecture for Generative Adversarial Networks
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Analyzing and Improving the Image Quality of StyleGAN
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The combining classifier: to train or not to train?
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Implementing Multi-class Classifiers by One-class Classification Methods
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Synthetic data augmentation using GAN for improved liver lesion classification
inferredcites →https://doi.org/10.1109/lsp.2018.2889273openalex-extracted
One-Class Convolutional Neural Network
inferredcites →https://doi.org/10.1109/maes.2004.1263230openalex-extracted
Class-specific classifier: avoiding the curse of dimensionality
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Inverting the Generator of a Generative Adversarial Network
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Toward Open Set Recognition
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Fully Convolutional Networks for Semantic Segmentation
inferredcites →https://doi.org/10.1145/1541880.1541882openalex-extracted
Anomaly detection
inferredcites →https://doi.org/10.1145/3065386openalex-extracted
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/335191.335388openalex-extracted
LOF
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Nonlinear Component Analysis as a Kernel Eigenvalue Problem
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One-class kernel subspace ensemble for medical image classification
inferredcites →https://doi.org/10.1186/s40537-021-00514-xopenalex-extracted
A literature review on one-class classification and its potential applications in big data
inferredcites →https://doi.org/10.1609/aaai.v25i1.8090openalex-extracted
Heterogeneous Transfer Learning for Image Classification
inferredcites →https://doi.org/10.1613/jair.105openalex-extracted
Solving Multiclass Learning Problems via Error-Correcting Output Codes
inferredcites →https://doi.org/10.3233/ida-150420openalex-extracted
Combining diverse one-class classifiers by means of dynamic weighted average for multi-class pattern classification
inferredcites →https://doi.org/10.3354/cr030079openalex-extracted
Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance
inferredcites →https://doi.org/10.48550/arxiv.1312.6114openalex-extracted
Auto-Encoding Variational Bayes
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-extracted
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-extracted
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
inferredcites →https://doi.org/10.48550/arxiv.1511.08060openalex-extracted
An open access repository of images on plant health to enable the development of mobile disease diagnostics
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Progressive Growing of GANs for Improved Quality, Stability, and Variation
inferredcites →https://doi.org/10.48550/arxiv.1810.10863openalex-extracted
GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1908.01878openalex-extracted
How Does Learning Rate Decay Help Modern Neural Networks?
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PyTorch: An Imperative Style, High-Performance Deep Learning Library
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Denoising Diffusion Probabilistic Models
inferredcites →https://doi.org/10.48550/arxiv.2101.03064openalex-extracted
One-Class Classification: A Survey
inferredcites →https://doi.org/10.48550/arxiv.2110.14051openalex-extracted
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges
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Fully Convolutional Networks for Semantic Segmentation
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