19,997 machine learning datasets
19,997 dataset results
This dataset includes 720 directional B-format RIRs, i.e. first-order Ambisonic room impulse responses, measured at 30 receiver positions with 1m spacing in an equidistant grid (4xm) with 24 hemispherical source positions each. The measurements were carried out at the IEM CUBE using Soundfield ST450 MKII microphones. The data is saved according to the SOFA convention (https://www.sofaconventions.org/mediawiki/index.php). The SOFA Matlab/Octave API is available at https://github.com/sofacoustics/API_MO.5. Unfortunately, the used SOFA convention (MultiPerspectiveAmbisonicRIR) was never integrated into the official SOFA conventions. However, it can be found at: https://github.com/jdemuynke/API_MO/tree/master/API_MO/conventions.
Presented stimuli of the listening experiment performed in the course of the master's thesis: K. Müller, "Variable-perspective rendering of virtual acoustic environments based on distributed first-order room impulse responses" and the article: K. Müller and F. Zotter, “Auralization based on multi-perspective ambisonic room impulse responses” (DOI: 10.1051/aacus/2020024).
This paper introduces a new large-scale dataset for Farsi document images, named SUT, which aims to tackle the challenges associated with obtaining diverse and substantial ground-truth data for supervised models in document image analysis (DIA) tasks, like document image classification, text detection and recognition, and information retrieval. The dataset comprises 62,453 images that have been categorized into 21 distinct classes, including identity documents featuring synthetically generated personal information superimposed on various backgrounds. The dataset also includes corresponding files with labeling information for the images. The ground-truth data is organized in CSV files containing image file paths and associated information about the embedded data.
A representative event-based eye-tracking dataset, collected with two event cameras mounted on a glass frame. It features variable recording lengths and event counts from 30 volunteers, providing an ideal benchmark for modeling the heterogeneity of event-based eye tracking in real-world scenarios.
A pioneering dataset for vignette removal. Vigset includes 983 pairs of both vignetting and vignetting-free high-resolution (5340×3697) real-world images under various conditions.
The scales of the data accessible through internet search engines can reach hundreds of millions, or even billions. The existence of such large weak-labeled databases has gained importance in the training of face recognition algorithms. Starting with the publicly available YFCC100M, we propose a weakly-labeled subset for multi-label face recognition for self-supervised methods. A 392K image subset of YFCC100M of 128x128 images was obtained by querying for the 40 facial attributes. We made this dataset publicly available.
Description This repository includes the experiment results, source code, and test data for Three Cs risk inference, using the CIRO (COVID-19 Infection Risk Ontology) and HermiT.
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MapReader in GeoHumanities workshop (SIGSPATIAL 2022): Gold standards and outputs
Automating the creation of catalogues for radio galaxies in next-generation deep surveys necessitates the identification of components within extended sources and their respective infrared hosts. We present RadioGalaxyNET, a multimodal dataset, tailored for machine learning tasks to streamline the automated detection and localization of multi-component extended radio galaxies and their associated infrared hosts. The dataset encompasses 4,155 instances of galaxies across 2,800 images, incorporating both radio and infrared channels. Each instance furnishes details about the extended radio galaxy class, a bounding box covering all components, a pixel-level segmentation mask, and the keypoint position of the corresponding infrared host galaxy. RadioGalaxyNET is the first dataset to include images from the highly sensitive Australian Square Kilometre Array Pathfinder (ASKAP) radio telescope, corresponding infrared images, and instance-level annotations for galaxy detection.
The problem here is to predict whether a share price will show an exceptional rise after quarterly announcement of the Earning Per Share based on the price movement of that share price on the proceeding 60 days? The data was formatted by Vlad Pazenuks as part of his third year project. Daily price data on NASDAQ 100 companies was extracted from a Kaggle data set. Reporting dates of these companies were obtained from NASDAQ.com. Each data is the percentage change of the close price from the day before. Each case is a series of 60 day data. The target class is is defined as 0 = price did not increase after company report release by more than 5 percent 1 = price increased after company report release by more than 5 percent There are 1931 cases, 1326 class 0 and 605 class 1.
Urdu News Headlines Dataset with VOA and BBC An Urdu news headlines dataset is a collection of news headlines in the Urdu language, typically scraped from news websites and social media platforms. These datasets can be valuable for researchers and developers working on a variety of tasks, such as:
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Synthetic dataset comprising three different environments for multi-camera dynamic novel view synthesis for soccer. This dataset is made compatible for Nerfstudio, and includes data parsers with various settings to reproduce the settings of our paper "Dynamic NeRFs for Soccer Scenes" and more.
For each problem, we provide 4 variants of prompts:
Data obtained by ray-tracing simulation in Herald Square. Data includes all the channel parameter information such as pathloss, delay, and angles.
BOTH57M is a body-hand dataset with body-level text prompts and finger-level text prompts.
CORE-MM is an Open-ended VQA benchmark dataset specifically designed for MLLMs, with a focus on complex reasoning tasks. CORE-MM benchmark consists of 279 manually curated reasoning questions, associated with a total of 342 images. The questions are divided into 3 reasoning categories--Deductive, Abductive and Analogical. 49 questions pertain to abductive reasoning, 181 require deductive reasoning, and 49 involve analogicalreasoning. Furthermore, the dataset is divided into two folds based on reasoning complexity, with 108 classified as “High” reasoning complexity and 171 as “Moderate” reasoning complexity.
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topex-printer is a dataset containing 102 machine parts of a label printing machine. It includes these parts for two domains, real photos and CAD rendered models.