Omkar2118/datasets huggingface dataset:
EMC Dutch Clinical Corpus

EMC Dutch clinical corpus contains four types of anonymized clinical documents: entries from general practitioners, specialists’ letters, radiology reports, and discharge letters. The identified UMLS terms in the corpus are annotated for negation, temporality, and experiencer properties.

Zubair Afzal, Ewoud Pons, Ning Kang, Miriam CJM Sturkenboom, Martijn J Schuemie, Jan A Kors. ContextD: an algorithm to identify contextual properties of medical terms in a Dutch clinical corpus. BMC Bioinformatics 2014, 15:373 doi:10.1186/s12859-014-0373-3
OSDD
Full name: Object State Detection Dataset

The   Objects States Detection Dataset consists of images depicting everyday household objects in a number of different states. The ground-truth annotations  involve the labels and bounding boxes spanning 18 object categories and 9 state classes. 
The object categories are: \textit{bottle, jar, tub, book, drawer, door, cup, mug, glass, bowl, basket, box, phone, charger, socket, towel, shirt} and \textit{newspaper}. The 9 state classes are: \textit{open, close, empty, containing something liquid (CL), containing something solid (CS), plugged, unplugged, folded} and \textit{unfolded}.

The images were obtained by selecting video frames   from the something-something V2 Dataset~\url{https://developer.qualcomm.com/software/ai-datasets/something-something}.
Specifically, images containing visually salient objects and states of the aforementioned categories were captured and annotated with bounding-boxes and ground truth labels referring to the corresponding object categories and state classes. Overall, the dataset contains  13,744 images and 19,018 annotations obtained by selecting the first, last and middle frames of 9,015 videos, after checking that each of them contains salient information.
Online Novel Recommendation Dataset

A dataset for online novel recommendation.

Introducing paper: Modeling User Repeat Consumption Behavior for Online Novel Recommendation
PKU SketchRe-ID Dataset
Full name: PKU SketchRe-ID Dataset

The PKU Sketch Re-ID dataset is constructed by National Engineering Laboratory for Video Technology (NELVT), Peking University.

The dataset contains 200 persons, each of which has one sketch and two photos. Photos of each person were captured during daytime by two cross-view cameras. We cropped the raw images (or video frames) manually to make sure that every photo contains the one specific person. We have a total of 5 artists to draw all persons’ sketches and every artist has his own painting style.
FaQuAD

The **FaQuAD** dataset is a **reading comprehension dataset** designed for evaluating question-answering models. Let me provide you with details about different versions of FaQuAD:

1. **FaQuAD (English)**:
    - **Description**: The original FaQuAD dataset follows the format of the **Stanford Question Answering Dataset (SQuAD)**.
    - **Content**: It comprises **900 questions** related to **249 reading passages**. These passages were extracted from **18 official documents** of a computer science college at a Brazilian federal university and **21 Wikipedia articles** related to the Brazilian higher education system³.
    - **Purpose**: Researchers use FaQuAD to develop and evaluate reading comprehension models in the domain of Brazilian higher education.
    - **GitHub Repository**: You can find the dataset and related code on the [FaQuAD GitHub repository](https://github.com/liafacom/faquad).

2. **FQuAD (French)**:
    - **Description**: FQuAD is a **French Native Reading Comprehension dataset** created by higher education students. It consists of **25,000+ questions** based on a set of Wikipedia articles.
    - **Similarity to SQuAD**: Like SQuAD, FQuAD provides annotated questions and answers for evaluation purposes.
    - **Website**: You can explore the FQuAD dataset on the [FQuAD website](https://fquad.illuin.tech/).

3. **FaQuAD (Portuguese)**:
    - **Description**: As far as we know, FaQuAD is a **pioneer Portuguese reading comprehension dataset** that follows the challenging format of SQuAD.
    - **Source**: The dataset includes passages from **official documents of a Brazilian computer science college** and **Wikipedia articles** related to Brazilian higher education.
    - **GitHub Repository**: The FaQuAD data and source code for experiments are available on the [FaQuAD GitHub repository](https://github.com/liafacom/faquad).

In summary, FaQuAD provides valuable resources for training and evaluating question-answering models across different languages and domains. Researchers can use these datasets to advance natural language understanding and improve machine comprehension systems.

Source: Conversation with Bing, 3/16/2024
(1) FaQuAD: Reading Comprehension Dataset in the Domain of ... - ResearchGate. https://www.researchgate.net/profile/Eraldo-Fernandes/publication/337789791_FaQuAD_Reading_Comprehension_Dataset_in_the_Domain_of_Brazilian_Higher_Education/links/5e825f5fa6fdcc139c173c8f/FaQuAD-Reading-Comprehension-Dataset-in-the-Domain-of-Brazilian-Higher-Education.pdf.
(2) GitHub - liafacom/faquad: FaQuAD reading comprehension dataset and .... https://github.com/liafacom/faquad.
(3) FQuAD. https://fquad.illuin.tech/.
(4) ruanchaves/faquad-nli · Datasets at Hugging Face. https://huggingface.co/datasets/ruanchaves/faquad-nli.
(5) FaQuAD: Reading Comprehension Dataset in the Domain of ... - GitHub. https://github.com/liafacom/faquad?search=1.
A-AVA
Full name: Actor-identified Spatiotemporal Action Detection

A new Actor-identified A-AVA dataset based on the existing AVA dataset and the TAO dataset, by assigning the unique actor identity and actions to each actor.

Introducing paper: Actor-identified Spatiotemporal Action Detection --- Detecting Who Is Doing What in Videos