PathMNIST statistics and PCA
收藏NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/14589090
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资源简介：
PathMNIST (64x64 resolution) mean (mean_reshaped.npy) and standard deviation (std_reshaped.npy) calculated on the training set;
PathMNIST's covariance matrix's (64x64 resolution) eigenvalues (eigenvalues.npy), the ratio of total variance explained by each principal component (eigenvalues_ratio.npy) and PathMNIST's principal components (pc_matrix.npy) computed using the normalized training dataset.
These items were computed from the PathMNIST dataset [1] and there used in [2].
[1] Yang, Jiancheng, et al. "Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification." Scientific Data 10.1 (2023): 41.
[2] Alice Bizeul, Thomas M. Sutter, Alain Ryser, Julius Von Kügelgen, Bernhard Schölkopf, Julia E. Vogt. Components Beat Patches: Eigenvector Masking for Visual Representation Learning. Oct, 2024.
创建时间：
2025-01-02
