Omkar2118/datasets huggingface dataset:
IATOS Dataset

Archivos con audios de toses de personas grabadas por celular, segmentados por COVID positivo y negativo según resultado de test RT-PCR.

Introducing paper: IATos: AI-powered pre-screening tool for COVID-19 from cough audio samples
Orchard
Full name: A Benchmark For Measuring Systematic Generalization of Multi-Hierarchical Reasoning

Orchard is a diagnostic dataset for systematically evaluating hierarchical reasoning in state-of-the-art neural sequence models

Introducing paper: ORCHARD: A Benchmark For Measuring Systematic Generalization of Multi-Hierarchical Reasoning
GVFC
Full name: Gun Violence Frame Corpus

This is a new dataset of news headlines and their frames related to the issue of gun violence in the United States. This Gun Violence Frame Corpus (GVFC) was curated and annotated by journalism and communication experts. The articles in this dataset are drawn from a sample of news articles from a list of 30 top U.S. news websites defined in terms of traffic to the websites; and collected from four time periods over the course of 2018 in order to capture a diversity of articles.

We include in this dataset, headlines of news articles and their annotations, the accompanying images and text- and image-derived features. We also include the codebook protocol, which includes all of the variables for annotations and their definitions that are applied by the annotators.

Introducing paper: Detecting Frames in News Headlines and Its Application to Analyzing News Framing Trends Surrounding U.S. Gun Violence
A dataset of neonatal EEG recordings with seizures annotations

Neonatal seizures are a common emergency in the neonatal intensive care unit (NICU). There are many questions yet to be answered regarding the temporal/spatial characteristics of seizures from different pathologies, response to medication, effects on neurodevelopment and optimal detection. This dataset contains EEG recordings from human neonates and the visual interpretation of the EEG by the human expert. Multi-channel EEG was recorded from 79 term neonates admitted to the neonatal intensive care unit (NICU) at the Helsinki University Hospital. The median recording duration was 74 minutes (IQR: 64 to 96 minutes). EEGs were annotated by three experts for the presence of seizures. An average of 460 seizures were annotated per expert in the dataset, 39 neonates had seizures by consensus and 22 were seizure free by consensus. The dataset can be used as a reference set of neonatal seizures, for the development of automated methods of seizure detection and other EEG analysis, as well as for the analysis of inter-observer agreement.
MIS-Check Dam
Full name: Minor Irrigation Structures- Check Dam

Minor Irrigation Structures Check-Dam Dataset is a public dataset annotated by domain experts using images from Google static map for instance segmentation and object detection tasks.

Google drive link for the dataset:
https://drive.google.com/drive/u/2/folders/16-XNaD6Cfbec7cpJB9_raYz8tl0CEQzZ

Introducing paper: The MIS Check-Dam Dataset for Object Detection and Instance Segmentation Tasks
MSU Video Alignment and Retrieval Benchmark Suite
Full name: MSU Video Alignment and Retrieval Benchmark Suite

Frame-to-frame video alignment/synchronization
Manually annotated 3-digit occupation codes from the Norwegian 1950 census

Manually annotated 3-digit occupation codes from the Norwegian full count 1950 population census.

Introducing paper: Lessons learned developing and using a machine learning model to automatically transcribe 2.3 million handwritten occupation codes
Manually annotated 3-digit occupation code training set from the Norwegian 1950 census

The Norwegian Historical Data Centre, 2021, "Manually annotated 3-digit occupation code training set from the Norwegian 1950 census", https://doi.org/10.18710/7JWAZX, DataverseNO, V1

Introducing paper: Lessons learned developing and using a machine learning model to automatically transcribe 2.3 million handwritten occupation codes
DeepSport Dataset

This basketball dataset was acquired under the Walloon region project DeepSport, using the Keemotion system installed in multiple arenas.
We would like to thanks both Keemotion for letting us use their system for raw image acquisition during live productions, and the LNB for the rights on their images.

Introducing paper: Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup
CNTD
Full name: Chinese and Naxi text detection

Chinese and Naxi scene text detection data set, labelme to json.

Source:[CNTD](https://github.com/yddcode/yolo-keras/tree/main/VOCdevkit/VOC2007)
IIIT5k

The IIIT5K dataset contains 5,000 text instance images: 2,000 for training and 3,000 for testing. It contains words from street scenes and from originally-digital images. Every image is associated with a 50 -word lexicon and a 1,000 -word lexicon.
SVTP

SVTP dataset stands for Scene Text Recognition Datasets. It is a collection of 4 popular Latin/English scene text recognition datasets, namely IIIT5K, SVT, SVTP, and CUTE-80. These datasets only provide case-insensitive annotations and no punctuation marks.
CUTE80

The CUTE80 dataset is a lightweight collection of images specifically designed for text detection in natural scene images. It contains a total of 13,000 annotated page images across five different popular categories: 1) Table 2) Figure 3) Natural image 4) Logo 5) ignature
Olivetti face
Full name: Olivetti face

This dataset contains a set of face images taken between April 1992 and April 1994 at AT&T Laboratories Cambridge.