19,997 machine learning datasets
19,997 dataset results
10000 instances of three-view numerical data set with 4 clusters and 2 feature components are considered. The data points in each view are generated from a 2-component 2-variate Gaussian mixture model (GMM) where their mixing proportions $\alpha_1^{(1)}=\alpha_1^{(2)}=\alpha_1^{(3)}=\alpha_1^{(4)}=0.3$; $\alpha_2^{(1)}=\alpha_2^{(2)}=\alpha_2^{(3)}=\alpha_2^{(4)}=0.15$; $\alpha_3^{(1)}=\alpha_3^{(2)}=\alpha_3^{(3)}=\alpha_3^{(4)}=0.15$ and $\alpha_4^{(1)}=\alpha_4^{(2)}=\alpha_4^{(3)}=\alpha_4^{(4)}=0.4$. The means $\mu_{ik}^{(1)}$ for the first view are $[-10 ~-5)]$,$[-9 ~ 11]$, $[0~ 6]$ and $[4~0]$; The means $\mu_{ik}^{(2)}$ for the view 2 are $[-8 ~-12]$,$[-6 ~ -3]$, $[-2~ 7]$ and $[2~1]$; And the means $\mu_{ik}^{(3)}$ for the third view are $[-5 ~-10]$,$[-8 ~ -1]$, $[0~ 5]$ and $[5~-4]$. The covariance matrices for the three views are $\Sigma_1^{(1)}=\Sigma_1^{(2)}=\Sigma_1^{(3)}=\Sigma_1^{(4)}=\left[ \begin{array}{cc} 1 & 0\0&1\end{array}\right]$; $\Sigma_2^{(1)}=\Si
Brazilian Sign Language (Libras) data set with 20 signs for sign language and gesture recognition benchmark:
A multimodal LIBRAS-UFOP Brazilian sign language dataset of minimal pairs using a microsoft Kinect senso.
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Simulation data and pre-trained Graph Neural Network (GNN) models produced in [1].
It contains 900 audio clips, annotated into 4 quadrants, according to Russell's model.
A large-scale dataset for proactive document retrieval that consists of over 2.8 million conversations from Reddit.
https://drive.google.com/drive/folders/1ykFXI9AJjrRCmz7MvjdqdCq7e-4Hir-c
Dataset Summary
SEN2VENµS is an open dataset for the super-resolution of Sentinel-2 images by leveraging simultaneous acquisitions with the VENµS satellite. The dataset is composed of 10m and 20m cloud-free surface reflectance patches from Sentinel-2, with their reference spatially-registered surface reflectance patches at 5 meters resolution acquired on the same day by the VENµS satellite. This dataset covers 29 locations with a total of 132 955 patches of 256x256 pixels at 5 meters resolution, and can be used for the training of super-resolution algorithms to bring spatial resolution of 8 of the Sentinel-2 bands down to 5 meters.
With the global availability of Multispectral Instrument (MSI, on-board Sentinel-2 satellite) data and Operational Land Imager (OLI, on-board Landsat-8 satellite) data which have 10 m and 30 m ground sample distance (GSD), respectively, it is conceivable that we can construct a dataset of LR-HR image pairs with OLI data as the LR image and MSI data as the HR image. This dataset, termed OLI2MSI, is a collection of paired real-world multisensor LR-HR data by carefully selecting relatively cloud-free MSI and OLI image in the same location obtained within a suitable temporal window.
SoccerNet-Echoes: A Soccer Game Audio Commentary Dataset.
CinePile is a question-answering-based, long-form video understanding dataset. It has been created using advanced large language models (LLMs) with human-in-the-loop pipeline leveraging existing human-generated raw data. It consists of approximately 300,000 training data points and 5,000 test data points.
Dataset Description
Online web communities often face bans for violating platform policies, encouraging their migration to alternative platforms. This migration, however, can result in increased toxicity and unforeseen consequences on the new platform. In recent years, researchers have collected data from many alternative platforms, indicating coordinated efforts leading to offline events, conspiracy movements, hate speech propagation, and harassment. Thus, it becomes crucial to characterize and understand these alternative platforms. To advance research in this direction, we collect and release a large-scale dataset from Scored -- an alternative Reddit platform that sheltered banned fringe communities, for example, c/TheDonald (a prominent right-wing community) and c/GreatAwakening (a conspiratorial community). Over four years, we collected approximately 57M posts from Scored, with at least 58 communities identified as migrating from Reddit and over 950 communities created since the platform's inception.
EchoNet-Dynamic is a dataset of over 10k echocardiogram, or cardiac ultrasound, videos from unique patients at Stanford University Medical Center. Each apical-4-chamber video is accompanied by an estimated ejection fraction, end-systolic volume, end-diastolic volume, and tracings of the left ventricle performed by an advanced cardiac sonographer and reviewed by an imaging cardiologist.
The dataset includes source code vulnerabilities in some of the most commonly used IoT frameworks. We introduce IoTvulCode- a novel framework consisting of a dataset-generating tool, and ML-enabled methods for the detection of source code vulnerabilities and weaknesses as well as the initial release of an IoT vulnerability dataset. Our framework contributes to improving the existing coding practices, leading to a more secure IoT infrastructure.
SunspotsYoloDataset is a set of 1690+380+128 high-resolution RGB astronomical images captured with smart telescopes with specific solar filters and annotated with the positions of sunspots that are effectively in the images. Two instruments were used for several months from Luxembourg and France between January 2023 and May 2024: a Stellina smart telescope (https://vaonis.com/stellina) and a Vespera smart telescope (https://vaonis.com/vespera).
We present the SJTU Multispectral Object Detection (SMOD) dataset for detection. The dataset has 8676 infrared visible image pairs. Within this dataset, 8042 pedestrians, 10478 riders, 6501 bicycles, and 6422 cars are annotated. The degree of occlusion of all objects is meticulously annotated. The dataset with low sampling rate has dense rider and pedestrian objects and contains rich illumination variations in its 3298 pairs of images of night scenarios.
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