SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 2471–2480 of 3304 papers

TitleStatusHype
2D+3D facial expression recognition via embedded tensor manifold regularization—0
2D Face Recognition System Based on Selected Gabor Filters and Linear Discriminant Analysis LDA—0
Two-stage dimension reduction for noisy high-dimensional images and application to Cryogenic Electron Microscopy—0
3D Face Recognition with Sparse Spherical Representations—0
3-Dimensional residual neural architecture search for ultrasonic defect detection—0
3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching—0
3D Structural Phenotype of the Optic Nerve Head at the Intersection of Glaucoma and Myopia - A Key to Improving Glaucoma Diagnosis in Myopic Populations—0
ABACUS: Unsupervised Multivariate Change Detection via Bayesian Source Separation—0
ABC-FL: Anomalous and Benign client Classification in Federated Learning—0
ABID: Angle Based Intrinsic Dimensionality—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified