19,997 machine learning datasets
19,997 dataset results
Heteroatom doped graphene supercapacitor feature data is gathered from various literatures for use in machine learning tasks. Main motivation is to optimize supercapacitors and to gain knowledge into models for electrochemistry tasks.
Studying how human drivers react differently when following autonomous vehicles (AV) vs. human-driven vehicles (HV) is critical for mixed traffic flow. This dataset contains extracted and enhanced two categories of car-following data, HV-following-AV (H-A) and HV-following-HV (H-H), from the open Lyft level-5 dataset.
Hyperspectral data for a MA/FA lead iodide perovskite gradient.
Controlled 2-hour degradation optical time series data for a MA/FA lead iodide perovskite gradient.
Intrinsic component extension of MIT Multi-Illumination Dataset proposed in the paper "Intrinsic Image Decomposition via Ordinal Shading", Chris Careaga and Yağız Aksoy, ACM Transactions on Graphics, 2023
The EyeInfo Dataset is an open-source eye-tracking dataset created by Fabricio Batista Narcizo, a research scientist at the IT University of Copenhagen (ITU) and GN Audio A/S (Jabra), Denmark. This dataset was introduced in the paper "High-Accuracy Gaze Estimation for Interpolation-Based Eye-Tracking Methods" (DOI: 10.3390/vision5030041). The dataset contains high-speed monocular eye-tracking data from an off-the-shelf remote eye tracker using active illumination. The data from each user has a text file with data annotations of eye features, environment, viewed targets, and facial features. This dataset follows the principles of the General Data Protection Regulation (GDPR).
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
The Beijing Traffic Dataset collects traffic speeds at 5-minute granularity for 3126 roadway segments in Beijing between 2022/05/12 and 2022/07/25.
Semi-inductive link prediction (LP) in knowledge graphs (KG) is the task of predicting facts for new, previously unseen entities based on context information. Although new entities can be integrated by retraining the model from scratch in principle, such an approach is infeasible for large-scale KGs, where retraining is expensive and new entities may arise frequently. In this paper, we propose and describe a large-scale benchmark to evaluate semi-inductive LP models. The benchmark is based on and extends Wikidata5M: It provides transductive, k-shot, and 0-shot LP tasks, each varying the available information from (i) only KG structure, to (ii) including textual mentions, and (iii) detailed descriptions of the entities. We report on a small study of recent approaches and found that semi-inductive LP performance is far from transductive performance on long-tail entities throughout all experiments. The benchmark provides a test bed for further research into integrating context and textual
We collect the various forms of Federal Reserve communications.
IMO-level geometry problem with complete natural language description, geometric shapes, formal language annotations, and theorem sequences annotations.
https://drive.google.com/file/d/1X_JTfD8Ch-IxmG5VHtKk_xGZT336Fl1Q/view?usp=drive_link
We introduce a RGB+S dataset named “Industrial Human Action Recognition Dataset” (InHARD) from a real-world setting for industrial human action recognition with over 2 million frames, collected from 16 distinct subjects. This dataset contains 13 different industrial action classes and over 4800 action samples. The introduction of this dataset should allow us the study and development of various learning techniques for the task of human actions analysis inside industrial environments involving human robot collaborations.
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
UHGEvalDataset contains over 5000 news items. It can be used in hallucination evaluation or detection tasks.
A dataset composed of 308 medium sized fires from the years 2018-2021, complete with both time series airborne based inference and ground operational estimation of fire extent, and operational mitigation data such as control line construction.
Video samples recorded in the field using the Azure Kinect DK. These videos are part of the AK-FRAEX software to demonstrate the use of frame extraction tasks. Visit the project site:
The CryoPPP dataset consists of 34 ground truth data and metadata for 335 EMPIAR IDs. The ground truth data is comprised of a variety of 9893 Micrographs (~300 cryo-EM images per EMPIAR ID) with manually curated ground truth coordinates of picked protein particles. The metadata consists of 1,698,802 high-resolution micrographs deposited in EMPIAR with their respective FPT and Globus data download paths.