72 datasets found

Mnist has a training set of 10000 examples, and the first four categories(0-3) of it, i.e., the first 4000 samples form a subset called Mnist4. It is divided into 4 categories...

The dataset used for out-of-distribution detection through soft clustering with non-negative kernel regression.

The dataset used in this paper is a collection of 9600 incomplete data sets, each with 10 variables and 25-200 individuals, with varying levels of missing values.

The MNIST dataset is used to demonstrate the clustering capability of the proposed group-sparse autoencoder.

Breast cancer dataset where mammograms have been labeled independently by three doctors. Ground-truth has been obtained through a biopsy, not available to the algorithm nor the...

Deep embeddings answer one simple question: How similar are two images? Learning these embeddings is the bedrock of verification, zero-shot learning, and visual search.

Clustering is a fundamental task in data analysis. Recently, deep clustering, which derives inspiration primarily from deep learning approaches, achieves state-of-the-art...

The shuttle dataset is used for anomaly clustering and visualization. It contains 9 numerical attributes and 7 classes.

The dataset is used to evaluate the performance of clustering algorithms.

The proposed k-meansNet is used for clustering and has explicit interpretability in structure.

Autoencoders with Intrinsic Dimension Constraints for Learning Low Dimensional Image Representations

The Houston model jointly considers all three features: documents' content, time of publication relative to other publications, and position of the spreader in the network.

The dataset used in the paper is a synthetic 2D dataset generated from a Gaussian Mixture Model.

The dataset used in the paper is a synthetic 2D dataset generated from a Gaussian Mixture Model.

The dataset used for the first nonlinear equalizer in optical communications using the traditional Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm...

The dataset used in the paper is a real dataset containing 122 time series representing the evolution, during a mission, of the altitude of a helicopter.

A synthetic dataset for evaluating the performance of T-Phenotype.

Balanced clustering problems with an additional requirement as a tree-like structure over the obtained balanced clusters. This kind of clustering problems can be useful in some...

Deep embedded image clustering with transformer and distribution information

Deep spectral clustering using dual autoencoder network