# Face and Expression Recognition

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/face-and-expression-recognition/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the application of various machine learning and dimensionality reduction techniques to the field of face recognition. It covers topics such as feature selection, support vector machines, ensemble methods, local binary patterns, non-negative matrix factorization, spectral clustering, Laplacian eigenmaps, and sparse representation in the context of face recognition. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t10057 |
| Works | 177 |

## Topic papers all

Showing 15 of 177.

- [Regularization Paths for Generalized Linear Models via Coordinate Descent](https://scholariq.org/papers/regularization-paths-for-generalized-linear-models-via-coordinate-descent/)
- [Online Learning for Matrix Factorization and Sparse Coding](https://scholariq.org/papers/online-learning-for-matrix-factorization-and-sparse-coding/)
- [Sparse Representation for Computer Vision and Pattern Recognition](https://scholariq.org/papers/sparse-representation-for-computer-vision-and-pattern-recognition/)
- [Linear discriminant analysis: A detailed tutorial](https://scholariq.org/papers/linear-discriminant-analysis-a-detailed-tutorial/)
- [Selecting critical features for data classification based on machine learning methods](https://scholariq.org/papers/selecting-critical-features-for-data-classification-based-on-machine-learning/)
- [Co-regularized Multi-view Spectral Clustering](https://scholariq.org/papers/co-regularized-multi-view-spectral-clustering/)
- [A survey of kernel and spectral methods for clustering](https://scholariq.org/papers/a-survey-of-kernel-and-spectral-methods-for-clustering/)
- [Facing Imbalanced Data--Recommendations for the Use of Performance Metrics](https://scholariq.org/papers/facing-imbalanced-data-recommendations-for-the-use-of-performance-metrics/)
- [A Co-training Approach for Multi-view Spectral Clustering](https://scholariq.org/papers/a-co-training-approach-for-multi-view-spectral-clustering/)
- [Advanced Spectral Classifiers for Hyperspectral Images: A review](https://scholariq.org/papers/advanced-spectral-classifiers-for-hyperspectral-images-a-review/)
- [The FERET evaluation methodology for face-recognition algorithms](https://scholariq.org/papers/the-feret-evaluation-methodology-for-face-recognition-algorithms/)
- [A Hybrid Feature Extraction Method With Regularized Extreme Learning Machine for Brain Tumor Classification](https://scholariq.org/papers/a-hybrid-feature-extraction-method-with-regularized-extreme-learning-machine-for/)
- [Face recognition using temporal image sequence](https://scholariq.org/papers/face-recognition-using-temporal-image-sequence/)
- [Robust principal component analysis for computer vision](https://scholariq.org/papers/robust-principal-component-analysis-for-computer-vision/)
- [Locally Weighted Ensemble Clustering](https://scholariq.org/papers/locally-weighted-ensemble-clustering/)

## Topic primary papers

Showing 15 of 64.

- [Regularization Paths for Generalized Linear Models via Coordinate Descent](https://scholariq.org/papers/regularization-paths-for-generalized-linear-models-via-coordinate-descent/)
- [Linear discriminant analysis: A detailed tutorial](https://scholariq.org/papers/linear-discriminant-analysis-a-detailed-tutorial/)
- [Selecting critical features for data classification based on machine learning methods](https://scholariq.org/papers/selecting-critical-features-for-data-classification-based-on-machine-learning/)
- [Co-regularized Multi-view Spectral Clustering](https://scholariq.org/papers/co-regularized-multi-view-spectral-clustering/)
- [The FERET evaluation methodology for face-recognition algorithms](https://scholariq.org/papers/the-feret-evaluation-methodology-for-face-recognition-algorithms/)
- [Face recognition using temporal image sequence](https://scholariq.org/papers/face-recognition-using-temporal-image-sequence/)
- [Facial expression recognition using radial encoding of local Gabor features and classifier synthesis](https://scholariq.org/papers/facial-expression-recognition-using-radial-encoding-of-local-gabor-features-and/)
- [Multi-View Clustering in Latent Embedding Space](https://scholariq.org/papers/multi-view-clustering-in-latent-embedding-space/)
- [The FERET evaluation methodology for face-recognition algorithms](https://scholariq.org/papers/the-feret-evaluation-methodology-for-face-recognition-algorithms-2/)
- [Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition](https://scholariq.org/papers/dive-into-ambiguity-latent-distribution-mining-and-pairwise-uncertainty/)
- [Feature Selection by Maximizing Independent Classification Information](https://scholariq.org/papers/feature-selection-by-maximizing-independent-classification-information/)
- [An Efficient Segmentation and Classification System in Medical Images Using Intuitionist Possibilistic Fuzzy C-Mean Clustering and Fuzzy SVM Algorithm](https://scholariq.org/papers/an-efficient-segmentation-and-classification-system-in-medical-images-using/)
- [A method for speeding up feature extraction based on KPCA](https://scholariq.org/papers/a-method-for-speeding-up-feature-extraction-based-on-kpca/)
- [Incremental learning of feature space and classifier for face recognition](https://scholariq.org/papers/incremental-learning-of-feature-space-and-classifier-for-face-recognition/)
- [A new LDA-based face recognition system which can solve the small sample size problem](https://scholariq.org/papers/a-new-lda-based-face-recognition-system-which-can-solve-the-small-sample-size/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.