19,997 machine learning datasets
19,997 dataset results
The Iranis Dataset is a Large-scale dataset of Farsi license plate characters containing a large-scale dataset with more than 83,000 images of Farsi numbers and letters collected from real-world license plate images captured by various cameras.
TLFM dataset structured in sequences of at least nine timesteps. The dataset includes 9696 images of both brightfield and green fluorescent protein channels at a resolution of 256 × 256. Dataset for multi-domain (BF and GFP) microscopy image sequence generation.
The Istella LETOR full dataset is composed of 33,018 queries and 220 features representing each query-document pair. It consists of 10,454,629 examples labeled with relevance judgments ranging from 0 (irrelevant) to 4 (perfectly relevant). The average number of per-query examples is 316. It has been splitted in train and test sets according to a 80%-20% scheme.
This is a paraphrasing dataset created using the adversarial paradigm. A task was designed called the Adversarial Paraphrasing Task (APT) whose objective was to write sentences that mean the same as a given sentence but have as different syntactical and lexical properties as possible.
Revision: v1.0.0-full-20210527a DOI: 10.5281/zenodo.4817662 Authors: J. Chazalon, E. Carlinet, Y. Chen, J. Perret, C. Mallet, B. Duménieu and T. Géraud Official competition website: https://icdar21-mapseg.github.io/
We scraped the 53 most popular C# repositories from GitHub and extracted all commits since the beginning of the project’s history. From each commit, we extracted edits in C# files along with the edits in their surrounding context.
This dataset contains the results of a depression screening experiment using two instruments: The PHQ-9 depression screening questionnaire and the chabot Perla.
SaRNet is a single class dataset consisting of tiles of satellite imagery labeled with potential 'targets'. Labelers were instructed to draw boxes around anything they suspect may a paraglider wing, missing in a remote area of Nevada. Volunteers were shown examples of similar objects already in the environment for comparison.
A random sample of 200 machine learning publications, systematically analyzed by a team of labelers, who asked up to 15 questions about how the publication discusses its training data. More documentation in data/README.md.
Data related to 1040 patients with Covid-19 admitted to hospitals in Iran have been collected. These patients were randomly selected from patients admitted to hospitals in Rasht, Tehran, and Bojnord. Of these 1040 patients, 375 of them are female, and 665 of them are male. Also, the age of these people is between 14 and 91 years, and the average age is about 54 years.
The dataset contains the following data from successful and failed executions of the Toyota HSR robot placing a book on a shelf.
The Reasonable Crowd dataset is a dataset to evaluate autonomous driving in a limited operating domain. The data consists of 92 traffic scenarios, with multiple ways of traversing each scenario. Multiple annotators expressed their preference between pairs of scenario traversals.
BH-rPPG dataset (stands for Beihang University Remote PhotoPlethysmoGraphy) is a dataset consists of 3 lighting conditions with uneven distribution which collected in indoor environment. In order to evaluate the performance of deep learning based rPPG under different lighting conditions, we recruited twelve healthy subjects (11 males and 1 females) on campus, with a mean age of 32, SD of 2.5.
IRLCov19 is a multilingual Twitter dataset related to Covid-19 collected in the period between February 2020 to July 2020 specifically for regional languages in India. It contains more than 13 million tweets.
TinyVIRAT-v2 is a benchmark dataset for recognizing real-world low-resolution activities present in videos. The dataset is comprised of naturally occuring low-resolution actions. This is an extension of the TinyVIRAT dataset and consists of actions with multiple labels. The videos are extracted from security videos which makes them realistic and more challenging.
The ARPA-E funded TERRA-REF project is generating open-access reference datasets for the study of plant sensing, genomics, and phenomics. Sensor data were generated by a field scanner sensing platform that captures color, thermal, hyperspectral, and active flourescence imagery as well as three dimensional structure and associated environmental measurements. This dataset is provided alongside data collected using traditional field methods in order to support calibration and validation of algorithms used to extract plot level phenotypes from these datasets.
The DBP2.0 dataset can be downloaded from the figshare repository. It has three entity alignment settings, i.e., ZH-EN, JA-EN and FR-EN. Each setting has the following files:
SyDog is a synthetic dataset of dogs containing ground truth pose and bounding box coordinates which was generated using the game engine, Unity.
HR-Crime is a subset of the UCF-Crime dataset suitable for human-related anomaly detection tasks.
The Uzbek speech corpus (USC) comprises 958 different speakers with a total of 105 hours of transcribed audio recordings. This is the first open-source Uzbek speech corpus dedicated to the ASR task.