dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
NuCLS | The NuCLS dataset contains over 220,000 labeled nuclei from breast cancer images from TCGA. These nuclei were annotated through the collaborative effort of pathologists, pathology residents, and medical students using the Digital Slide Archive. These data can be used in several ways to develop and validate algorithms f... | Provide a detailed description of the following dataset: NuCLS |
K-Hairstyle | K-hairstyle is a novel large-scale Korean hairstyle dataset with 256,679 high-resolution images. In addition, K-hairstyle contains various hair attributes annotated by Korean expert hair stylists and hair segmentation masks. | Provide a detailed description of the following dataset: K-Hairstyle |
CC12M | Conceptual 12M (CC12M) is a dataset with 12 million image-text pairs specifically meant to be used for vision-and-language pre-training. | Provide a detailed description of the following dataset: CC12M |
ACDC | The goal of the **Automated Cardiac Diagnosis Challenge (ACDC)** challenge is to:
- compare the performance of automatic methods on the segmentation of the left ventricular endocardium and epicardium as the right ventricular endocardium for both end diastolic and end systolic phase instances;
- compare the performa... | Provide a detailed description of the following dataset: ACDC |
MoNuSeg | The dataset for this challenge was obtained by carefully annotating tissue images of several patients with tumors of different organs and who were diagnosed at multiple hospitals. This dataset was created by downloading H&E stained tissue images captured at 40x magnification from TCGA archive. H&E staining is a routine... | Provide a detailed description of the following dataset: MoNuSeg |
GlaS | The dataset used in this challenge consists of 165 images derived from 16 H&E stained histological sections of stage T3 or T42 colorectal adenocarcinoma. Each section belongs to a different patient, and sections were processed in the laboratory on different occasions. Thus, the dataset exhibits high inter-subject varia... | Provide a detailed description of the following dataset: GlaS |
Brain US | This brain anatomy segmentation dataset has 1300 2D US scans for training and 329 for testing. A total of 1629 in vivo B-mode US images were obtained from 20 different subjects (age<1 years old) who were treated between 2010 and 2016. The dataset contained subjects with IVH and without (healthy subjects but in risk of ... | Provide a detailed description of the following dataset: Brain US |
PieAPP dataset | The PieAPP dataset is a large-scale dataset used for training and testing perceptually-consistent image-error prediction algorithms.
The dataset can be downloaded from: [server containing a zip file with all data](https://web.ece.ucsb.edu/~ekta/projects/PieAPPv0.1/all_data_PieAPP_dataset_CVPR_2018.zip) (2.2GB) or [Go... | Provide a detailed description of the following dataset: PieAPP dataset |
AbstRCT - Neoplasm | The AbstRCT dataset consists of randomized controlled trials retrieved from the MEDLINE database via PubMed search. The trials are annotated with argument components and argumentative relations.
Paper: [Transformer-Based Argument Mining for Healthcare Applications](https://hal.archives-ouvertes.fr/hal-02879293/) | Provide a detailed description of the following dataset: AbstRCT - Neoplasm |
CDCP | The Cornell eRulemaking Corpus – CDCP is an argument mining corpus annotated with argumentative structure information capturing the evaluability of arguments. The corpus consists of 731 user comments on Consumer Debt Collection Practices (CDCP) rule by the Consumer Financial Protection Bureau (CFPB); the resulting data... | Provide a detailed description of the following dataset: CDCP |
DRI Corpus | The **Dr. Inventor Multi-Layer Scientific Corpus** (**DRI Corpus**) includes 40 Computer Graphics papers, selected by domain experts. Each paper of the Corpus has been annotated by three annotators by providing the following layers of annotations, each one characterizing a core aspect of scientific publications:
* S... | Provide a detailed description of the following dataset: DRI Corpus |
PIPAL | PIPAL training set contains 200 reference images, 40 distortion types, 23k distortion images, and more than one million human ratings. Especially, we include GAN-based algorithms’ outputs as a new GAN-based distortion type. We employ the Elo rating system to assign the Mean Opinion Scores (MOS). | Provide a detailed description of the following dataset: PIPAL |
PWDB | # Overview
This database of simulated arterial pulse waves is designed to be representative of a sample of pulse waves measured from healthy adults. It contains pulse waves for 4,374 virtual subjects, aged from 25-75 years old (in 10 year increments). The database contains a baseline set of pulse waves for each of t... | Provide a detailed description of the following dataset: PWDB |
ReCAM | Tasks
Our shared task has three subtasks. Subtask 1 and 2 focus on evaluating machine learning models' performance with regard to two definitions of abstractness (Spreen and Schulz, 1966; Changizi, 2008), which we call imperceptibility and nonspecificity, respectively. Subtask 3 aims to provide some insights to their ... | Provide a detailed description of the following dataset: ReCAM |
VQA-E | VQA-E is a dataset for Visual Question Answering with Explanation, where the models are required to generate and explanation with the predicted answer. The VQA-E dataset is automatically derived from the VQA v2 dataset by synthesizing a textual explanation for each image-question-answer triple.
Image Source: [VQA-E:... | Provide a detailed description of the following dataset: VQA-E |
RSPECT | **The RSNA Pulmonary Embolism CT** (**RSPECT**) Dataset is composed of CT pulmonary angiogram images and annotations related to pulmonary embolism. It's part of the 2020 RSNA Pulmonary Embolism Detection Challenge which invited researchers to develop machine-learning algorithms to detect and characterize instances of p... | Provide a detailed description of the following dataset: RSPECT |
SEP-28k | Stuttering Events in Podcasts (SEP-28k) is a dataset containing over 28k clips labeled with five event types including blocks, prolongations, sound repetitions, word repetitions, and interjections. Audio comes from public podcasts largely consisting of people who stutter interviewing other people who stutter. | Provide a detailed description of the following dataset: SEP-28k |
FluencyBank | **FluencyBank** is a shared database for the study of fluency development. Participants include typically-developing monolingual and bilingual children, children and adults who stutter (C/AWS) or who clutter (C/AWC), and second language learners.
Image Source: [FluencyBank](https://fluency.talkbank.org/) | Provide a detailed description of the following dataset: FluencyBank |
MHIST | The **m**inimalist **hist**opathology image analysis dataset (**MHIST**) is a binary classification dataset of 3,152 fixed-size images of colorectal polyps, each with a gold-standard label determined by the majority vote of seven board-certified gastrointestinal pathologists. MHIST also includes each image’s annotator ... | Provide a detailed description of the following dataset: MHIST |
CC-News | **CommonCrawl News** is a dataset containing news articles from news sites all over the world. The dataset is available in form of Web ARChive (WARC) files that are released on a daily basis. | Provide a detailed description of the following dataset: CC-News |
MalNet | MalNet is a large public graph database, representing a large-scale ontology of software function call graphs. MalNet contains over 1.2 million graphs, averaging over 17k nodes and 39k edges per graph, across a hierarchy of 47 types and 696 families.
Image Source: [Expore MalNet](https://mal-net.org/explore) | Provide a detailed description of the following dataset: MalNet |
IBM-Rank-30k | The IBM-Rank-30k is a dataset for the task of argument quality ranking. It is a corpus of 30,497 arguments carefully annotated for point-wise quality.
Image Source: [A Large-scale Dataset for Argument Quality Ranking: Construction and Analysis](https://arxiv.org/pdf/1911.11408v1.pdf) | Provide a detailed description of the following dataset: IBM-Rank-30k |
OTEANNv3 | This dataset contains orthographic samples of words in 19 languages (ar, br, de, en, eno, ent, eo, es, fi, fr, fro, it, ko, nl, pt, ru, sh, tr, zh). Each sample contains two text features: a Word (the textual representation of the word according to its orthography) and a Pronunciation (the highest-surface IPA pronuncia... | Provide a detailed description of the following dataset: OTEANNv3 |
Maintenance of Wakefulness Test (MWT) recordings | Maintenance of Wakefulness Test (MWT) is a dataset of recordings with microsleep episodes and drowsiness.
Cite as:
Hertig-Godeschalk Anneke, Skorucak Jelena, Malafeev Alexander, Achermann Peter, Mathis Johannes, & Schreier David R. (2019). Maintenance of Wakefulness Test (MWT) recordings (Version v1) [Data set]. Ze... | Provide a detailed description of the following dataset: Maintenance of Wakefulness Test (MWT) recordings |
darpa_sd2_perovskites | Included in this content:
* 0045.perovksitedata.csv - main dataset used in this article. A more detailed description can be found in the “dataset overview” section below
* Chemical Inventory.csv - the hand curated file of all chemicals used in the construction of the perovskite dataset. This file includes ide... | Provide a detailed description of the following dataset: darpa_sd2_perovskites |
Decagon | Bio-decagon is a dataset for polypharmacy side effect identification problem framed as a multirelational link prediction problem in a two-layer multimodal graph/network of two node types: drugs and proteins. Protein-protein interaction
network describes relationships between proteins. Drug-drug interaction network con... | Provide a detailed description of the following dataset: Decagon |
TREC-10 | A question type classification dataset with 6 classes for questions about a person, location, numeric information, etc. The test split has 500 questions, and the training split has 5452 questions.
Paper: [Learning Question Classifiers](https://www.aclweb.org/anthology/C02-1150/) | Provide a detailed description of the following dataset: TREC-10 |
Deep Thermal Imaging Dataset | The **Deep Thermal Imaging dataset** consists of two main datasets:
- **DeepTherm I** (Indoor materials) - 15 indoor materials were used to create the dataset DeepTherm I which consists of 14,860 processed thermal images (average count of data for each individual class: 990.7, SD=425.9; 400-600 images of each materi... | Provide a detailed description of the following dataset: Deep Thermal Imaging Dataset |
Fluent Speech Commands | Fluent Speech Commands is an open source audio dataset for spoken language understanding (SLU) experiments. Each utterance is labeled with "action", "object", and "location" values; for example, "turn the lights on in the kitchen" has the label {"action": "activate", "object": "lights", "location": "kitchen"}. A model ... | Provide a detailed description of the following dataset: Fluent Speech Commands |
Endotect Polyp Segmentation Challenge Dataset | A challenge that consists of three tasks, each targeting a different requirement for in-clinic use. The first task involves classifying images from the GI tract into 23 distinct classes. The second task focuses on efficiant classification measured by the amount of time spent processing each image. The last task relates... | Provide a detailed description of the following dataset: Endotect Polyp Segmentation Challenge Dataset |
Medico automatic polyp segmentation challenge (dataset) | The “Medico automatic polyp segmentation challenge” aims to develop computer-aided diagnosis systems for automatic polyp segmentation to detect all types of polyps (for example, irregular polyp, smaller or flat polyps) with high efficiency and accuracy. The main goal of the challenge is to benchmark semantic segmentati... | Provide a detailed description of the following dataset: Medico automatic polyp segmentation challenge (dataset) |
WIT | **Wikipedia-based Image Text** (**WIT**) Dataset is a large multimodal multilingual dataset. WIT is composed of a curated set of 37.6 million entity rich image-text examples with 11.5 million unique images across 108 Wikipedia languages. Its size enables WIT to be used as a pretraining dataset for multimodal machine le... | Provide a detailed description of the following dataset: WIT |
Unsplash Dataset | The Unsplash Dataset is created by over 200,000 contributing photographers and billions of searches across thousands of applications, uses, and contexts. It contains over 2M Unsplash images. | Provide a detailed description of the following dataset: Unsplash Dataset |
IDRiD | Indian Diabetic Retinopathy Image Dataset (IDRiD) dataset consists of typical diabetic retinopathy lesions and normal retinal structures annotated at a pixel level. This dataset also provides information on the disease severity of diabetic retinopathy and diabetic macular edema for each image. This dataset is perfect f... | Provide a detailed description of the following dataset: IDRiD |
ReDWeb | The ReDWeb dataset consists of 3600 RGB-RD image pairs collected from the Web. This dataset covers a wide range of scenes and features various non-rigid objects. | Provide a detailed description of the following dataset: ReDWeb |
HRWSI | The HRWSI dataset consists of about 21K diverse high-resolution RGB-D image pairs derived from the Web stereo images. Also, it provides sky segmentation masks, instance segmentation masks as well as invalid pixel masks. | Provide a detailed description of the following dataset: HRWSI |
Fongbe audio | Fongbe Data collected by Fréjus A. A LALEYE
This dataset contains Fongbe speech corpus with audio data and transcriptions. | Provide a detailed description of the following dataset: Fongbe audio |
DeepFluoroLabeling-IPCAI2020 | This collection contains data and code associated with the IPCAI/IJCARS 2020 paper “Automatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration.” The data hosted here consists of annotated datasets of actual hip fluoroscopy, CT and derived data from six lower torso cadaveric specimens... | Provide a detailed description of the following dataset: DeepFluoroLabeling-IPCAI2020 |
Lens Flare Dataset | The Lens Flare dataset is an internal dataset for Flare Spot detection used in the paper "Automatic Flare Spot Artifact Detection and Removal in Photographs" by Patricia Vitoria and Coloma Ballester.
The dataset consists of 405 natural images in which a minimum of one flare spot artifact appears. The sources of ligh... | Provide a detailed description of the following dataset: Lens Flare Dataset |
SARA motion | Sara motion is a 3D motion dataset, named Synthetic Actors and Real Actions (SARA), for training a model to produce motion embeddings suitable for reasoning about motion similarity.
The motion sequence data for this dataset was generated by combining 18 different actors (i.e., action performing characters). The cha... | Provide a detailed description of the following dataset: SARA motion |
NTU RGB+D 120 motion similarity | Motion similarity annotations for [NTU RGB+D 120 dataset](https://paperswithcode.com/dataset/ntu-rgb-d-120) to evaluate motion similarity in the real world. | Provide a detailed description of the following dataset: NTU RGB+D 120 motion similarity |
BU-BIL | **BU-BIL** is an image library which includes six datasets that represent three imaging modalities and six object types. Providers of the datasets are instructed to choose images that capture the various environmental conditions and imaging noise that arose in their studies. These experts are asked to then select objec... | Provide a detailed description of the following dataset: BU-BIL |
MTA-KDD'19 | Malware Traffic Analysis Knowledge Dataset 2019 (MTA-KDD'19) is an updated and refined dataset specifically tailored to train and evaluate machine learning based malware traffic analysis algorithms. To generate it, that authors started from the largest databases of network traffic captures available online, deriving a ... | Provide a detailed description of the following dataset: MTA-KDD'19 |
Cuff-Less Blood Pressure Estimation | ##Data Set Information:
The main goal of this data set is providing clean and valid signals for designing cuff-less blood pressure estimation algorithms. The raw electrocardiogram (ECG), photoplethysmograph (PPG), and arterial blood pressure (ABP) signals are originally collected from the physionet.org and then some... | Provide a detailed description of the following dataset: Cuff-Less Blood Pressure Estimation |
POTUS Corpus | The **POTUS Corpus** is a Database of Weekly Addresses for the Study of Stance in Politics and Virtual Agents.
One of the main challenges in the field of Embodied Conversational Agent (ECA) is to generate socially believable agents. The common strategy for agent behaviour synthesis is to rely on dedicated corpus ana... | Provide a detailed description of the following dataset: POTUS Corpus |
ImageNet VIPriors subset | The training and validation data are subsets of the training split of the Imagenet 2012. The test set is taken from the validation split of the Imagenet 2012 dataset. Each data set includes 50 images per class. | Provide a detailed description of the following dataset: ImageNet VIPriors subset |
BiRD | **Bigram Relatedness Dataset** (**BiRD**) is a large, fine-grained, bigram relatedness dataset, using a comparative annotation technique called Best Worst Scaling. Each of BiRD's 3,345 English term pairs involves at least one bigram. BiRD is made freely available to foster further research on how meaning can be represe... | Provide a detailed description of the following dataset: BiRD |
Shiny dataset | The shiny folder contains 8 scenes with challenging view-dependent effects used in our paper. We also provide additional scenes in the shiny_extended folder.
The test images for each scene used in our paper consist of one of every eight images in alphabetical order.
Each scene contains the following directory stru... | Provide a detailed description of the following dataset: Shiny dataset |
MATH | MATH is a new dataset of 12,500 challenging competition mathematics problems. Each problem in MATH has a full step-by-step solution which can be used to teach models to generate answer derivations and explanations. | Provide a detailed description of the following dataset: MATH |
PhysioNet Challenge 2016 | Introduction
The 2016 PhysioNet/CinC Challenge aims to encourage the development of algorithms to classify heart sound recordings collected from a variety of clinical or nonclinical (such as in-home visits) environments. The aim is to identify, from a single short recording (10-60s) from a single precordial location, ... | Provide a detailed description of the following dataset: PhysioNet Challenge 2016 |
IXI | **IXI Dataset** is a collection of 600 MR brain images from normal, healthy subjects. The MR image acquisition protocol for each subject includes:
* T1, T2 and PD-weighted images
* MRA images
* Diffusion-weighted images (15 directions)
The data has been collected at three different hospitals in London:
*... | Provide a detailed description of the following dataset: IXI |
LIFULL HOME'S | The National Institute of Informatics provides LIFULL HOME'S Dataset to researchers, which was offered by [LIFULL Co., Ltd.](https://lifull.com/en/) for promoting research in informatics and the related fields.
The dataset contains the data of [LIFULL HOME'S](https://www.homes.co.jp/), a Real Estate Information Serv... | Provide a detailed description of the following dataset: LIFULL HOME'S |
CosmoFlow | The latest CosmoFlow dataset includes around 10,000 cosmological N-body dark matter simulations. The simulations are run using MUSIC to generate the initial conditions, and are evolved with pyCOLA, a multithreaded Python/Cython N-body code. The output of these simulations is then binned into a 3D histogram of particle ... | Provide a detailed description of the following dataset: CosmoFlow |
Sketch2aia (Mobile User Interface Sketches) | Dataset of 374 photos of hand-drawn sketches of App Inventor apps used for development of the Sketch2aia model for automatic generation of App Inventor wireframes from hand-drawn sketches.
Data format
Training:2 37 images in JPG (.jpg) format with 720×1280 pixels, each accompanied by a JSON (.json) file with manual... | Provide a detailed description of the following dataset: Sketch2aia (Mobile User Interface Sketches) |
An Amharic News Text classification Dataset | In NLP, text classification is one of the primary problems we try to solve and its uses in language analyses are indisputable. The lack of labeled training data made it harder to do these tasks in low resource languages like Amharic. The task of collecting, labeling, annotating, and making valuable this kind of data wi... | Provide a detailed description of the following dataset: An Amharic News Text classification Dataset |
PHOENIX14T | Over a period of three years (2009 - 2011) the daily news and weather forecast airings of the German public tv-station PHOENIX featuring sign language interpretation have been recorded and the weather forecasts of a subset of 386 editions have been transcribed using gloss notation. Furthermore, we used automatic speech... | Provide a detailed description of the following dataset: PHOENIX14T |
CUAD | **Contract Understanding Atticus Dataset** (**CUAD**) is a dataset for legal contract review. CUAD was created with dozens of legal experts from The Atticus Project
and consists of over 13,000 annotations. The task is to highlight salient portions of a contract that are important for a human to review. | Provide a detailed description of the following dataset: CUAD |
BIKED | **BIKED** is a dataset comprised of 4500 individually designed bicycle models sourced from hundreds of designers. BIKED enables a variety of data-driven design applications for bicycles and generally supports the development of data-driven design methods. The dataset is comprised of a variety of design information incl... | Provide a detailed description of the following dataset: BIKED |
THEOStereo | THEOStereo is a dataset providing synthetic stereo image pairs and their corresponding scene depth and will be published along with [1]. All images follow the omnidirectional camera model. In total, there are *31,250* omnidirectional images pairs. The training set contains *25,000* image pairs. For validation and testi... | Provide a detailed description of the following dataset: THEOStereo |
PCD | The Arabic dataset is scraped mainly from الموسوعة الشعرية and الديوان. After merging both, the total number of verses is 1,831,770 poetic verses. Each verse is labeled by its meter, the poet who wrote it, and the age which it was written in. There are 22 meters, 3701 poets and 11 ages: Pre-Islamic, Islamic, Umayyad, M... | Provide a detailed description of the following dataset: PCD |
ARCH | **ARCH** is a computational pathology (CP) multiple instance captioning dataset to facilitate dense supervision of CP tasks. Existing CP datasets focus on narrow tasks; ARCH on the other hand contains dense diagnostic and morphological descriptions for a range of stains, tissue types and pathologies. | Provide a detailed description of the following dataset: ARCH |
UASOL | The UASOL an RGB-D stereo dataset, that contains 160902 frames, filmed at 33 different scenes, each with between 2 k and 10 k frames. The frames show different paths from the perspective of a pedestrian, including sidewalks, trails, roads, etc. The images were extracted from video files with 15 fps at HD2K resolution w... | Provide a detailed description of the following dataset: UASOL |
SUM | SUM is a new benchmark dataset of semantic urban meshes which covers about 4 km2 in Helsinki (Finland), with six classes: Ground, Vegetation, Building, Water, Vehicle, and Boat.
The authors used Helsinki 3D textured meshes as input and annotated them as a benchmark dataset of semantic urban meshes. The Helsinki's ra... | Provide a detailed description of the following dataset: SUM |
BLURB | **BLURB** is a collection of resources for biomedical natural language processing. In general domains such as newswire and the Web, comprehensive benchmarks and leaderboards such as GLUE have greatly accelerated progress in open-domain NLP. In biomedicine, however, such resources are ostensibly scarce. In the past, the... | Provide a detailed description of the following dataset: BLURB |
GAD | **GAD**, or **Gene Associations Database**, is a corpus of gene-disease associations curated from genetic association studies. | Provide a detailed description of the following dataset: GAD |
BC2GM | Created by Smith et al. at 2008, the BioCreative II Gene Mention Recognition (BC2GM) Dataset contains data where participants are asked to identify a gene mention in a sentence by giving its start and end characters. The training set consists of a set of sentences, and for each sentence a set of gene mentions (GENE ann... | Provide a detailed description of the following dataset: BC2GM |
Kaggle EyePACS | Diabetic retinopathy is the leading cause of blindness in the working-age population of the developed world. It is estimated to affect over 93 million people.
retina
The US Center for Disease Control and Prevention estimates that 29.1 million people in the US have diabetes and the World Health Organization estima... | Provide a detailed description of the following dataset: Kaggle EyePACS |
THFOOD-50 | Fine-Grained Thai Food Image Classification Datasets
THFOOD-50 containing 15,770 images of 50 famous Thai dishes. | Provide a detailed description of the following dataset: THFOOD-50 |
SRD | SRD is a dataset for shadow removal that contains 3088 shadow and shadow-free image pairs. | Provide a detailed description of the following dataset: SRD |
BL30K | BL30K is a synthetic dataset rendered using Blender with ShapeNet's data. We break the dataset into six segments, each with approximately 5K videos. The videos are organized in a similar format as DAVIS and YouTubeVOS, so dataloaders for those datasets can be used directly. Each video is 160 frames long, and each frame... | Provide a detailed description of the following dataset: BL30K |
BIG | A high-resolution semantic segmentation dataset with 50 validation and 100 test objects. Image resolution in BIG ranges from 2048×1600 to 5000×3600. Every image in the dataset has been carefully labeled by a professional while keeping the same guidelines as PASCAL VOC 2012 without the void region. | Provide a detailed description of the following dataset: BIG |
COCO Object Detection VIPriors subset | The training and validation data are subsets of the training split of the MS COCO dataset (2017 release, bounding boxes only). The test set is taken from the validation split of the MS COCO dataset. | Provide a detailed description of the following dataset: COCO Object Detection VIPriors subset |
Cityscapes VIPriors subset | The training and validation data are subsets of the training split of the Cityscapes dataset. The test set is taken from the validation split of the Cityscapes dataset. | Provide a detailed description of the following dataset: Cityscapes VIPriors subset |
UCF-101 VIPriors subset | The VIriors Action Recognition Challenge uses a subset of the UCF101 action recognition dataset:
Train set: ~4.8K clips.
Validation set: ~4.7K clips.
Test set: ~3.8K clips. | Provide a detailed description of the following dataset: UCF-101 VIPriors subset |
CLEVR-Hans | The CLEVR-Hans data set is a novel confounded visual scene data set, which captures complex compositions of different objects. This data set consists of [CLEVR](clevr) images divided into several classes.
The membership of a class is based on combinations of objects’ attributes and relations. Additionally, certain ... | Provide a detailed description of the following dataset: CLEVR-Hans |
Tsinghua Dogs | Tsinghua Dogs is a fine-grained classification dataset for dogs, over 65% of whose images are collected from people's real life. Each dog breed in the dataset contains at least 200 images and a maximum of 7,449 images, basically in proportion to their frequency of occurrence in China, so it significantly increases the ... | Provide a detailed description of the following dataset: Tsinghua Dogs |
ADAM | ADAM is organized as a half day Challenge, a Satellite Event of the ISBI 2020 conference in Iowa City, Iowa, USA.
The ADAM challenge focuses on the investigation and development of algorithms associated with the diagnosis of Age-related Macular degeneration (AMD) and segmentation of lesions in fundus photos from AMD... | Provide a detailed description of the following dataset: ADAM |
DiCOVA | The DiCOVA Challenge dataset is derived from the Coswara dataset, a crowd-sourced dataset of sound recordings from COVID-19 positive and non-COVID-19 individuals. The Coswara data is collected using a web-application2, launched in April-2020, accessible through the internet by anyone around the globe. The volunteering ... | Provide a detailed description of the following dataset: DiCOVA |
Digital Peter | Digital Peter is a dataset of Peter the Great's manuscripts annotated for segmentation and text recognition. The dataset may be useful for researchers to train handwriting text recognition models as a benchmark for comparing different models. It consists of 9,694 images and text files corresponding to lines in historic... | Provide a detailed description of the following dataset: Digital Peter |
OGB-LSC | OGB Large-Scale Challenge (OGB-LSC) is a collection of three real-world datasets for advancing the state-of-the-art in large-scale graph ML. OGB-LSC provides graph datasets that are orders of magnitude larger than existing ones and covers three core graph learning tasks -- link prediction, graph regression, and node cl... | Provide a detailed description of the following dataset: OGB-LSC |
TeachMyAgent | TeachMyAgent (TA) is a benchmark for Automatic Curriculum Learning (ACL) algorithms leveraging procedural task generation. It includes 1) challenge-specific unit-tests using variants of a procedural Box2D bipedal walker environment, and 2) a new procedural Parkour environment combining most ACL challenges, making it id... | Provide a detailed description of the following dataset: TeachMyAgent |
L1000 | The **L1000** dataset consists of ~1,400,000 gene-expression profiles on the responses of ~50 human cell lines to one of ~20,000 compounds across a range of concentrations. The L1000 dataset and its normalization versions10 were recently widely used in drug repurposing and discovery.
Description from: [A deep learni... | Provide a detailed description of the following dataset: L1000 |
DSBEC | The data set consists of 6257 labeled images of Bose-Einstein condensates (BECs) with and without solitonic excitations, including kink solitons and solitonic vortices. Each element of the data set contains a masked image (132x164 pixels) of 2D atomic density used to train the machine learning model used in the paper "... | Provide a detailed description of the following dataset: DSBEC |
ConScenD | The ConScenD dataset consists of over 340 scenarios extracted from the naturalistic highway dataset highD. This scenarios can be used to test for the introduction of Level 3 Automated Lane Keeping Systems according to the UNECE R157 ALKS Regulation. | Provide a detailed description of the following dataset: ConScenD |
LDC2020T02 | Abstract Meaning Representation (AMR) Annotation Release 3.0 was developed by the Linguistic Data Consortium (LDC), SDL/Language Weaver, Inc., the University of Colorado's Computational Language and Educational Research group and the Information Sciences Institute at the University of Southern California. It contains a... | Provide a detailed description of the following dataset: LDC2020T02 |
KoDF | The Korean DeepFake Detection Dataset (KoDF) is a large-scale collection of synthesized and real videos focused on Korean subjects, used for the task of deepfake detection.
The dataset consists of 62,166 real videos and 175,776 fake videos from 403 subjects. The fake videos are created using 6 different methods: Fac... | Provide a detailed description of the following dataset: KoDF |
HDA Facial Tattoo and Painting Database | The Hochschule Darmstadt (HDA) facial tattoo and paintings database contains 500 pairs of facial images of individuals with and without facial tattoos or paintings. The database was collected from multiple online sources. | Provide a detailed description of the following dataset: HDA Facial Tattoo and Painting Database |
Gowalla | Gowalla is a location-based social networking website where users share their locations by checking-in. The friendship network is undirected and was collected using their public API, and consists of 196,591 nodes and 950,327 edges. We have collected a total of 6,442,890 check-ins of these users over the period of Feb. ... | Provide a detailed description of the following dataset: Gowalla |
DODa | Darija Open Dataset (**DODa**) is an open-source project for the Moroccan dialect. With more than 10,000 entries DODa is arguably the largest open-source collaborative project for Darija-English translation built for Natural Language Processing purposes. In fact, besides semantic categorization, DODa also adopts a synt... | Provide a detailed description of the following dataset: DODa |
LeT-Mi | Levantine Twitter dataset for Misogynistic language (LeT-Mi) is an Arabic Levantine Twitter dataset for misogynistic language to be the first benchmark dataset for Arabic misogyny.
⚠️ Note: To be made publicly available on Github | Provide a detailed description of the following dataset: LeT-Mi |
SVT | **The Street View Text** (**SVT**) dataset was harvested from Google Street View. Image text in this data exhibits high variability and often has low resolution. In dealing with outdoor street level imagery, we note two characteristics. (1) Image text often comes from business signage and (2) business names are easily ... | Provide a detailed description of the following dataset: SVT |
RETWEET | **RETWEET** is a dataset of tweets and overall predominant sentiment of their replies.
SUMMARY
------
**WHAT:** Message-level Polarity Classification.
**GOAL:** To predict the predominant sentiment among (potential) first-order replies to a given tweet.
**IDEA:** Mitigate the problem of lacking labeled train... | Provide a detailed description of the following dataset: RETWEET |
TRANCE | TRANCE extends CLEVR by asking a uniform question, i.e. what is the transformation between two given images, to test the ability of transformation reasoning. TRANCE includes three levels of settings, i.e. Basic (single-step transformation), Event (multi-step transformation), and View (multi-step transformation with var... | Provide a detailed description of the following dataset: TRANCE |
Sewer-ML | Sewer-ML is a sewer defect dataset. It contains 1.3 million images, from 75,618 videos collected from three Danish water utility companies over nine years. All videos have been annotated by licensed sewer inspectors following the Danish sewer inspection standard, Fotomanualen. This leads to consistent and reliable anno... | Provide a detailed description of the following dataset: Sewer-ML |
HW-NAS-Bench | HW-NAS-Bench is a dataset for HardWare-aware Neural Architecture Search (HW-NAS). It is the first dataset for HW-NAS research aiming to democratize HW-NAS research to non-hardware experts and facilitate a unified benchmark for HW-NAS to make HW-NAS research more reproducible and accessible, covering two SOTA NAS search... | Provide a detailed description of the following dataset: HW-NAS-Bench |
MMKG | MMKG is a collection of three knowledge graphs for link prediction and entity matching research. Contrary to other knowledge graph datasets, these knowledge graphs contain both numerical features and images for all entities as well as entity alignments between pairs of KGs. While MMKG is intended to perform relational ... | Provide a detailed description of the following dataset: MMKG |
UBI-Fights | UBI-Fights - Concerning a specific anomaly detection and still providing a wide diversity in fighting scenarios, the UBI-Fights dataset is a unique new large-scale dataset of 80 hours of video fully annotated at the frame level. Consisting of 1000 videos, where 216 videos contain a fight event, and 784 are normal daily... | Provide a detailed description of the following dataset: UBI-Fights |
SKAB | SKAB is designed for evaluating algorithms for anomaly detection. The benchmark currently includes 30+ datasets plus Python modules for algorithms’ evaluation. Each dataset represents a multivariate time series collected from the sensors installed on the testbed. All instances are labeled for evaluating the results of ... | Provide a detailed description of the following dataset: SKAB |
DF20 | Danish Fungi 2020 (DF20) is a fine-grained dataset and benchmark. The dataset, constructed from observations submitted to the Danish Fungal Atlas, is unique in its taxonomy-accurate class labels, small number of errors, highly unbalanced long-tailed class distribution, rich observation metadata, and well-defined class ... | Provide a detailed description of the following dataset: DF20 |
DF20 - Mini | Danish Fungi 2020 (DF20) is a novel fine-grained dataset and benchmark. The dataset, constructed from observations submitted to the Danish Fungal Atlas, is unique in its taxonomy-accurate class labels, small number of errors, highly unbalanced long-tailed class distribution, rich observation metadata, and well-defined ... | Provide a detailed description of the following dataset: DF20 - Mini |
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