19,997 machine learning datasets
19,997 dataset results
Vehicle-1M involves vehicle images captured across day and night, from head or rear, by multiple surveillance cameras installed in cities. There are totally 936,051 images from 55,527 vehicles and 400 vehicle models in the dataset. Each image is attached with a vehicle ID label denoting its identity in real world as well as a vehicle model label indicating the make, model and year of the vehicle(i.e. "Audi-A6-2013"). All publications using Vehicle-1M dataset should cite the paper below: Haiyun Guo, Chaoyang Zhao, Zhiwei Liu, Jinqiao Wang, Hanqing Lu: Learning coarse-to-fine structured feature embedding for vehicle re-identification. AAAI 2018.
The study of material corrosion is an important research area, with corrosion degradation of metallic structures causing expenses up to 4% of the global domestic product annually along with major safety risks worldwide. Unfortunately, large-scale and timely scientific discovery of materials has been hindered by the lack of standardized corrosion experimental data in the public domain for developing machine learning models. Obtaining such data is challenging due to the expert knowledge and time required to conduct these scientific experiments and assess corrosion levels. We curate a novel dataset consisting of 600 images annotated with expert corrosion ratings obtained over 10 years of laboratory corrosion testing by material scientists. Based on this data set, we find that non-experts even when rigorously trained with domain guidelines to rate corrosion fail to match expert ratings. Challenges include limited data, image artifacts, and millimeter-precision corrosion. This motivates us
Chinese and Naxi scene text detection data set, labelme to json.
Debate.org is a debate platform that is organized in rounds where each of two opponents submits posts arguing for their side.
The MEFB consists of a test set of 100 image pairs.
FAscicle Lower Leg Muscle Ultrasound Dataset is a dataset composed of 812 ultrasound images of lower leg muscles to analyze muscle weaknesses and prevent injuries. It combines the datasets provided by two articles, “Estimating Full Regional Skeletal Muscle Fibre Orientation from B-Mode Ultrasound Images Using Convolutional, Residual, and Deconvolutional Neural Networks” published by Ryan Cunningham et al. and “Automated Analysis of Musculoskeletal Ultrasound Images Using Deep Learning” published by Neil Cronin, with complementary annotations. The dataset has been introduced in this paper: Michard, H., Luvison, B., Pham, Q. C., Morales-Artacho, A. J., & Guilhem, G. (2021, August). AW-Net: automatic muscle structure analysis on B-mode ultrasound images for injury prevention. In Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (pp. 1-9).
This dataset defines a total of 11 crowd motion patterns and it is composed of over 6000 video sequences with an average length of 100 frames per sequence. This documentation presents how to download and process the Crowd-11 dataset.
Nepali News Corpus Raw nepali text scrapped from several online websites. Total file size of concatenated text file -> 4.6 GB. This raw text corpus can be used for tasks such as casual language modelling and masked language modelling.
This is a who-trust-whom online social network of a general consumer review site Epinions.com. Members of the site can decide whether to ''trust'' each other. All the trust relationships interact and form the Web of Trust which is then combined with review ratings to determine which reviews are shown to the user.
The COVID-19 CT dataset is constructed by Shenzhen Research Institute of Big Data (SRIBD), Future Network of Intelligence Institute (FNii) and CUHKSZ-JD Joint AI Lab, Chinese University of Hongkong, Shenzhen, China, which contains 368 medical findings in Chinese and 1,104 chest CT scans from the First Affiliated Hospital of Jinan University Guangzhou and the Fifth Affiliated Hospital of Sun Yat-sen University Zhuhai in China. Please see more details in our TNNLS paper - Medical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learning.
The Reddit COVID Dataset is a dataset of 4.51M Reddit posts and 17.8M comments - all mentions of COVID until 2021-10-25 across the entire Reddit social network. Both were procured with SocialGrep's export feature and released as part of SocialGrep Reddit datasets. The posts are labeled with their subreddit, title, creation date, domain, selftext, and score. The comments are labeled with their subreddit, body, creation date, sentiment (calculated for you using a VADER pipeline), and score.
The ASL-Skeleton3D introduces a representation based on mapping into the three-dimensional space the coordinates of the signers in the ASLLVD dataset. This enables a more accurate observation of the body parts and the signs articulation, allowing researchers to better understand the language and explore other approaches to the SLR field.
The ASL-Phono introduces a novel linguistics-based representation, which describes the signs in the ASLLVD dataset in terms of a set of attributes of the American Sign Language phonology.
H²O is an image dataset annotated for Human-to-human-or-object interaction detection. H²O is composed of the images from V-COCO dataset to which are added images which mostly contain interactions between people. The dataset has been introduced in this paper: Orcesi, A., Audigier, R., Toukam, F. P., & Luvison, B. (2021, December). Detecting Human-to-Human-or-Object (H 2 O) Interactions with DIABOLO. In 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021) (pp. 1-8). IEEE. The annotations were made with Pixano, an opensource, smart annotation tool for computer vision applications: https://pixano.cea.fr/
Crowd Violence \ Non-violence Database and benchmark: A database of real-world, video footage of crowd violence, along with standard benchmark protocols designed to test both violent/non-violent classification and violence outbreak detections. The data set contains 246 videos. All the videos were downloaded from YouTube. The shortest clip duration is 1.04 seconds, the longest clip is 6.52 seconds, and the average length of a video clip is 3.60 seconds.
We present sentence aligned parallel corpora across 10 Indian Languages - Hindi, Telugu, Tamil, Malayalam, Gujarati, Urdu, Bengali, Oriya, Marathi, Punjabi, and English - many of which are categorized as low resource. The corpora are compiled from online sources which have content shared across languages. The corpora presented significantly extends present resources that are either not large enough or are restricted to a specific domain (such as health). We also provide a separate test corpus compiled from an independent online source that can be independently used for validating the performance in 10 Indian languages. Alongside, we report on the methods of constructing such corpora using tools enabled by recent advances in machine translation and cross-lingual retrieval using deep neural network based methods.
28,943 Humphrey Visual Field (HVF) tests from 3,871 patients and 7,428 eyes.
InfiniteRep is a synthetic, open-source dataset for fitness and physical therapy (PT) applications. It includes 1k videos of diverse avatars performing multiple repetitions of common exercises. It includes significant variation in the environment, lighting conditions, avatar demographics, and movement trajectories. From cadence to kinematic trajectory, each rep is done slightly differently -- just like real humans. InfiniteRep videos are accompanied by a rich set of pixel-perfect labels and annotations, including frame-specific repetition counts.
Citation Request: See the articles for more detailed information on the data.
KOKLU Murat (a), UNLERSEN M. Fahri (b), OZKAN Ilker Ali (a), ASLAN M. Fatih(c), SABANCI Kadir (c)