datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Ar-MUSA
Data Directory Structure
The Ar-MUSA directory contains annotated datasets organized by batches and annotation teams. Each batch is labeled with a number, and the annotation team is indicated by a letter. The structure is as follows:
Ar-MUSA
├── Annotation 1a
│ ├── frames # Contains the extracted frames for each record
│ ├── audios # Contains the corresponding audio files
│ ├── transcripts # Contains the transcripts of the audio files
│ └── annotations.csv #… See the full description on the dataset page: https://huggingface.co/datasets/Skhaled/Ar-MUSA.ArMeme
ArMeme Dataset
Overview
ArMeme is the first multimodal Arabic memes dataset that includes both text and images, collected from various social media platforms. It serves as the first resource dedicated to Arabic multimodal research. While the dataset has been annotated to identify propaganda in memes, it is versatile and can be utilized for a wide range of other research purposes, including sentiment analysis, hate speech detection, cultural studies, meme generation, and… See the full description on the dataset page: https://huggingface.co/datasets/QCRI/ArMeme.OCTDL2024
Dataset Card for OCTDL2024
The OCTDL2024 dataset is a subset of the dataset OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods.
Citation
@article{kulyabin2024octdl,
title={OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods},
author={Kulyabin, Mikhail and Zhdanov, Aleksei and Nikiforova, Anastasia and Stepichev, Andrey
and Kuznetsova, Anna and Ronkin, Mikhail and Borisov, Vasilii and Bogachev… See the full description on the dataset page: https://huggingface.co/datasets/ArmisticeAI/OCTDL2024.