dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
Visiting Card | ID Card Images | Hindi-English | This dataset is an extremely challenging set of over 2000+ original Visiting card/ID card images captured and crowdsourced from over 300+ urban and rural areas, where each image is **manually reviewed and verified** by computer vision professionals at Datacluster Labs.
### **Dataset Features**
- Dataset size : ... | Provide a detailed description of the following dataset: Visiting Card | ID Card Images | Hindi-English |
Crowd in a rally | Crowd Counting | Crowd Human | This dataset is an extremely challenging set of over 3000+ original Crowd images captured and crowdsourced from over 300+ urban and rural areas, where each image is **manually reviewed and verified** by computer vision professionals at Datacluster Labs.
### **Dataset Features**
- Dataset size : 3000+
- Capture... | Provide a detailed description of the following dataset: Crowd in a rally | Crowd Counting | Crowd Human |
WALT | We introduce a new dataset, Watch and Learn Time-lapse (WALT), consisting of multiple (4K and 1080p) cameras capturing urban environments over a year. | Provide a detailed description of the following dataset: WALT |
Autorickshaw Image Dataset | Niche Vehicle Dataset | This dataset is an extremely challenging set of over 8000+ original Fire and Smoke images captured and crowdsourced from over 1200+ urban and rural areas, where each image is **manually reviewed and verified** by computer vision professionals at Datacluster Labs.
### **Dataset Features**
- Dataset size : 8000+
... | Provide a detailed description of the following dataset: Autorickshaw Image Dataset | Niche Vehicle Dataset |
Electronics Object Image Dataset | Computer Parts | This dataset is an extremely challenging set of over 5000+ original Electronic Items images captured and crowdsourced from over 1000+ urban and rural areas, where each image is **manually reviewed and verified** by computer vision professionals at Datacluster Labs.
### **Dataset Features**
- Dataset size : 5000... | Provide a detailed description of the following dataset: Electronics Object Image Dataset | Computer Parts |
Hindi Text Image Dataset | Hindi in the wild | This dataset is an extremely challenging set of over 5000+ original Hindi text images captured and crowdsourced from over 700+ urban and rural areas, where each image is **manually reviewed and verified** by computer vision professionals at DataclusterLabs.
### **Dataset Features**
- Dataset size : 5000+
- Cap... | Provide a detailed description of the following dataset: Hindi Text Image Dataset | Hindi in the wild |
Nasa Exoplanet Archive | The NASA Exoplanet Archive is an online astronomical exoplanet and stellar catalog and data service that collates and cross-correlates astronomical data and information on exoplanets and their host stars, and provides tools to work with these data. The archive is dedicated to collecting and serving important public dat... | Provide a detailed description of the following dataset: Nasa Exoplanet Archive |
RefMatte | RefMatte is the first large-scale challenging dataset under the task referring image matting, generated by a comprehensive image composition and expression generation engine on top of current public high-quality matting foregrounds with flexible logics and re-labelled diverse attributes. RefMatte consists of 230 objec... | Provide a detailed description of the following dataset: RefMatte |
Summaries of genetic variation | The dataset represents data generated from a commonly used model in population genetics. It comprises a matrix of 1,000,000 rows and 9 columns, representing parameters and summaries generated by an infinite-sites coalescent model for genetic variation. The first two columns encode the scaled mutation rate (theta) and s... | Provide a detailed description of the following dataset: Summaries of genetic variation |
TAT-QA | TAT-QA (Tabular And Textual dataset for Question Answering) is a large-scale QA dataset, aiming to stimulate progress of QA research over more complex and realistic tabular and textual data, especially those requiring numerical reasoning.
The unique features of TAT-QA include:
- The context given is hybrid, compr... | Provide a detailed description of the following dataset: TAT-QA |
DAST | This is an SDQC stance-annotated Reddit dataset for the Danish language generated within a thesis project. The dataset consists of over 5000 comments structured as comment trees and linked to 33 source posts.
The dataset is applicable for supervised stance classification and rumour veracity prediction. | Provide a detailed description of the following dataset: DAST |
KITTI-STEP | The Segmenting and Tracking Every Pixel (STEP) benchmark consists of 21 training sequences and 29 test sequences. It is based on the KITTI Tracking Evaluation and the Multi-Object Tracking and Segmentation (MOTS) benchmark. This benchmark extends the annotations to the Segmenting and Tracking Every Pixel (STEP) task. [... | Provide a detailed description of the following dataset: KITTI-STEP |
aidatatang_200zh | A Chinese Mandarin speech corpus by Beijing DataTang Technology Co., Ltd, containing 200 hours of speech data from 600 speakers. The transcription accuracy for each sentence is larger than 98%.
Aidatatang_200zh is a free Chinese Mandarin speech corpus provided by Beijing DataTang Technology Co., Ltd under Creative Com... | Provide a detailed description of the following dataset: aidatatang_200zh |
AnnoMI | # AnnoMI: A Dataset of Expert-Annotated Counselling Dialogues
## Dataset Introduction
Research on natural language processing approaches to analysing counselling dialogues has seen substantial development in recent years, but access to this area remains extremely limited, due to the lack of publicly available exp... | Provide a detailed description of the following dataset: AnnoMI |
Chest X-ray images | Chest X-ray images for pneumonia detection. | Provide a detailed description of the following dataset: Chest X-ray images |
SV-Ident | SV-Ident comprises 4,248 sentences from social science publications in English and German. The data is the official data for the Shared Task: “Survey Variable Identification in Social Science Publications” (SV-Ident) 2022. Sentences are labeled with variables that are mentioned either explicitly or implicitly.
The ... | Provide a detailed description of the following dataset: SV-Ident |
Minigrid | There are other gridworld Gym environments out there, but this one is designed to be particularly simple, lightweight and fast. The code has very few dependencies, making it less likely to break or fail to install. It loads no external sprites/textures, and it can run at up to 5000 FPS on a Core i7 laptop, which means ... | Provide a detailed description of the following dataset: Minigrid |
PolyU-BPCoMa | PolyU-BPCoMa: A Dataset and Benchmark Towards Mobile Colorized Mapping Using a Backpack Multisensorial System | Provide a detailed description of the following dataset: PolyU-BPCoMa |
IEIs | We would like to introduce three types of _ion and electron insulators_, i.e. _Li-ion & electron insulators_ (LEIs), _Na-ion & electron insulators_ (NEIs), and _K-ion & electron insulators_ (KEIs), and provide a set of codes here to screen candidate materials from computational material database, [Materials Project](ht... | Provide a detailed description of the following dataset: IEIs |
Hephaestus | Hephaestus is the first large-scale InSAR dataset. Driven by volcanic unrest detection, it provides 19,919 unique satellite frames annotated with a diverse set of labels. Moreover, each sample is accompanied by a textual description of its contents. The goal of this dataset is to boost research on exploitation of inter... | Provide a detailed description of the following dataset: Hephaestus |
CARLANE Benchmark | Unsupervised Domain Adaptation demonstrates great potential to mitigate domain shifts by transferring models from labeled source domains to unlabeled target domains. While Unsupervised Domain Adaptation has been applied to a wide variety of complex vision tasks, only few works focus on lane detection for autonomous dri... | Provide a detailed description of the following dataset: CARLANE Benchmark |
Hyperbard | Hyperbard is a dataset of diverse relational data representations derived from Shakespeare's plays. Our representations range from simple graphs capturing character co-occurrence in single scenes to hypergraphs encoding complex communication settings and character contributions as hyperedges with edge-specific node wei... | Provide a detailed description of the following dataset: Hyperbard |
Example dataset for CellCluster code | Dataset to be used with the https://github.com/MathBioCU/WSINDy_CellCluster code | Provide a detailed description of the following dataset: Example dataset for CellCluster code |
FixEval | We introduce FixEval , a dataset for competitive programming bug fixing along with a comprehensive test suite and show the necessity of execution based evaluation compared to suboptimal match based evaluation metrics like BLEU, CodeBLEU, Syntax Match, Exact Match etc. | Provide a detailed description of the following dataset: FixEval |
MICCAI'2015 Gland Segmentation Challenge Contest Dataset | MICCAI'2015 Gland Segmentation Challenge Contest Dataset
Welcome to the challenge on gland segmentation in histology images. This challenge was held in conjuction with MICCAI 2015, Munich, Germany.
Objective of the Challenge
We aim to bring together researchers who are interested in the gland segmentation problem,... | Provide a detailed description of the following dataset: MICCAI'2015 Gland Segmentation Challenge Contest Dataset |
JetClass | JetClass is a new large-scale dataset to facilitate deep learning research in particle physics. It consists of 100M particle jets for training, 5M for validation and 20M for testing. The dataset contains 10 classes of jets, simulated with [MadGraph](https://launchpad.net/mg5amcnlo) + [Pythia](https://pythia.org/) + [De... | Provide a detailed description of the following dataset: JetClass |
EVI | The EVI dataset is a challenging, multilingual spoken-dialogue dataset with 5,506 dialogues in English, Polish, and French. The dataset can be used to develop and benchmark conversational systems for user authentication tasks, i.e. speaker enrolment (E), speaker verification (V), speaker identification (I).
The data... | Provide a detailed description of the following dataset: EVI |
EEG and P300 database to determine the signal to noise ratio during a variety of realistic tasks | This database contains EEG and evoked potential recordings from 20 participants. This allows to assess the signal to noise ratio:
- Signal: The P300 power and VEP power can be used to assess the signal power
- Noise: The signal power consisting of EMG and baseline EEG during the different tasks allows to determine th... | Provide a detailed description of the following dataset: EEG and P300 database to determine the signal to noise ratio during a variety of realistic tasks |
HaGRID | We introduce a large image dataset **HaGRID** (**HA**nd **G**esture **R**ecognition **I**mage **D**ataset) for hand gesture recognition (HGR) systems. You can use it for image classification or image detection tasks. Proposed dataset allows to build HGR systems, which can be used in video conferencing services (Zoom, S... | Provide a detailed description of the following dataset: HaGRID |
GPA | multi-view imagery of people interacting with a variety of rich 3D environments | Provide a detailed description of the following dataset: GPA |
RPCD | The Reddit Photo Critique Dataset (RPCD) contains tuples of image and photo critiques. RPCD consists of __74K images__ and __220K comments__ and is collected from a Reddit community used by hobbyists and professional photographers to improve their photography skills by leveraging constructive community feedback.
The... | Provide a detailed description of the following dataset: RPCD |
OADAT | An experimental and synthetic (simulated) OA raw signals and reconstructed image domain datasets rendered with different experimental parameters and tomographic acquisition geometries.
For detailed information, see [github.com/berkanlafci/oadat](https://github.com/berkanlafci/oadat). | Provide a detailed description of the following dataset: OADAT |
Matlab code for the article: Model-based selection of most informative diagnostic tests and test parameters | Description TBC | Provide a detailed description of the following dataset: Matlab code for the article: Model-based selection of most informative diagnostic tests and test parameters |
Traditional and Context-specific Spam Twitter | This data set is being released to support the spam and context-specific spam detection tasks on Twitter data.
There are three sets of tweets, parenting-related, #MeToo-related (a social movement focused on tackling issues related to sexual harassment and sexual assault of women), and gun-violence-related tweets. Ea... | Provide a detailed description of the following dataset: Traditional and Context-specific Spam Twitter |
adVFed | Natural Vertical Partitioned CVR Dataset for Vertical Federated Learning
This Dataset repo provides 2 industrial CVR Dataset for VFL research. | Provide a detailed description of the following dataset: adVFed |
Time Series COVID-19 Sales | The dataset contains the hotel demand and revenue of 8 major tourist destinations in the US (e.g., Los Angeles, Orlando ...). The dataset contains sales, daily occupancy, demand, and revenue of the upper-middle class hotels.
We also gathered dynamic exogenous variables such as the state’s closure/open policy to enri... | Provide a detailed description of the following dataset: Time Series COVID-19 Sales |
COCO-MEBOW | COCO-MEBOW (Monocular Estimation of Body Orientation in the Wild) is a new large-scale dataset for orientation estimation from a single in-the-wild image. The body-orientation labels for 133380 human bodies within 55K images from the COCO dataset have been collected using an efficient and high-precision annotation pipe... | Provide a detailed description of the following dataset: COCO-MEBOW |
895 Fire Videos Data | Description:
895 Fire Videos Data，the total duration of videos is 27 hours 6 minutes 48.58 seconds. The dataset adpoted different cameras to shoot fire videos. The shooting time includes day and night.The dataset can be used for tasks such as fire detection.
Data size:
895 videos, the total duration is 27 hours 6 ... | Provide a detailed description of the following dataset: 895 Fire Videos Data |
5,011 Images – Human Frontal face Data (Male) | Description：
5,011 Images – Human Frontal face Data (Male). The data diversity includes multiple scenes, multiple ages and multiple races. This dataset includes 2,004 Caucasians , 3,007 Asians. This dataset can be used for tasks such as face detection, race detection, age detection, beard category classification.
D... | Provide a detailed description of the following dataset: 5,011 Images – Human Frontal face Data (Male) |
1,995 People Face Images Data (Asian race) | Description:
1,995 People Face Images Data (Asian race). For each subject, more than 20 images per person with frontal face were collected. This data can be used for face recognition and other tasks.
Data size:
1,995 people, more than 20 images per person with frontal face
Race distribution:
Asian people | Provide a detailed description of the following dataset: 1,995 People Face Images Data (Asian race) |
PRTiger | Dataset for automatic pull request title generation. | Provide a detailed description of the following dataset: PRTiger |
SportsMOT | ## Motivation
Multi-object tracking (MOT) is a fundamental task in computer vision, aiming to estimate objects (e.g., pedestrians and vehicles) bounding boxes and identities in video sequences.
Prevailing human-tracking MOT datasets mainly focus on pedestrians in crowded street scenes (e.g., [MOT17](https://motch... | Provide a detailed description of the following dataset: SportsMOT |
SRSD-Feynman (Easy set) | Our SRSD (Feynman) datasets are designed to discuss the performance of Symbolic Regression for Scientific Discovery. We carefully reviewed the properties of each formula and its variables in the Feynman Symbolic Regression Database to design reasonably realistic sampling range of values so that our SRSD datasets can be... | Provide a detailed description of the following dataset: SRSD-Feynman (Easy set) |
SRSD-Feynman (Hard set) | Our SRSD (Feynman) datasets are designed to discuss the performance of Symbolic Regression for Scientific Discovery. We carefully reviewed the properties of each formula and its variables in the Feynman Symbolic Regression Database to design reasonably realistic sampling range of values so that our SRSD datasets can be... | Provide a detailed description of the following dataset: SRSD-Feynman (Hard set) |
SRSD-Feynman (Medium set) | Our SRSD (Feynman) datasets are designed to discuss the performance of Symbolic Regression for Scientific Discovery. We carefully reviewed the properties of each formula and its variables in the Feynman Symbolic Regression Database to design reasonably realistic sampling range of values so that our SRSD datasets can be... | Provide a detailed description of the following dataset: SRSD-Feynman (Medium set) |
BN-HTRd | We introduce a new **Dataset** ([BN-HTRd](https://data.mendeley.com/datasets/743k6dm543)) for offline Handwritten Text Recognition (HTR) from images of Bangla scripts comprising words, lines, and document-level annotations. The BN-HTRd dataset is based on the BBC Bangla News corpus - which acted as ground truth texts f... | Provide a detailed description of the following dataset: BN-HTRd |
23 Pairs of Identical Twins Face Image Data | Description：
23 Pairs of Identical Twins Face Image Data. The collecting scenes includes indoor and outdoor scenes. The subjects are Chinese males and females. The data diversity inlcudes multiple face angles, multiple face postures, close-up of eyes, multiple light conditions and multiple age groups. This dataset can... | Provide a detailed description of the following dataset: 23 Pairs of Identical Twins Face Image Data |
105,941 Images Natural Scenes OCR Data of 12 Languages | Description:
105,941 Images Natural Scenes OCR Data of 12 Languages. The data covers 12 languages (6 Asian languages, 6 European languages), multiple natural scenes, multiple photographic angles. For annotation, line-level quadrilateral bounding box annotation and transcription for the texts were annotated in the data... | Provide a detailed description of the following dataset: 105,941 Images Natural Scenes OCR Data of 12 Languages |
4,458 People - 3D Facial Expressions Recognition Data | Description:
4,458 People - 3D Facial Expressions Recognition Data. The collection scenes include indoor scenes and outdoor scenes. The dataset includes males and females. The age distribution ranges from juvenile to the elderly, the young people and the middle aged are the majorities. The device includes iPhone X, iP... | Provide a detailed description of the following dataset: 4,458 People - 3D Facial Expressions Recognition Data |
10,000 People - Human Pose Recognition Data | Description:
10,000 People - Human Pose Recognition Data. This dataset includes indoor and outdoor scenes.This dataset covers males and females. Age distribution ranges from teenager to the elderly, the middle-aged and young people are the majorities. The data diversity includes different shooting heights, different a... | Provide a detailed description of the following dataset: 10,000 People - Human Pose Recognition Data |
WikiTables-TURL | The WikiTables-TURL dataset was constructed by the authors of [TURL](https://paperswithcode.com/paper/turl-table-understanding-through) and is based on the WikiTable corpus, which is a large collection of Wikipedia tables. The dataset consists of 580,171 tables divided into fixed training, validation and testing splits... | Provide a detailed description of the following dataset: WikiTables-TURL |
GitTables-SemTab | The GitTables-SemTab dataset is a subset of the [GitTables](https://paperswithcode.com/dataset/gittables) dataset and was created to be used during the [SemTab](http://www.cs.ox.ac.uk/isg/challenges/sem-tab/) challenge. The dataset consists of 1101 tables and is used to benchmark the Column Type Annotation (CTA) task. ... | Provide a detailed description of the following dataset: GitTables-SemTab |
Tough Tables | The ToughTables (2T) dataset was created for the [SemTab](http://www.cs.ox.ac.uk/isg/challenges/sem-tab/) challenge and includes 180 tables in total. The tables in this dataset can be categorized in two groups: the control (CTRL) group tables and tough (TOUGH) group tables.
The CTRL group contains 60 tables generat... | Provide a detailed description of the following dataset: Tough Tables |
50stateSimulations | Every decade following the Census, states and municipalities must redraw districts for Congress, state houses, city councils, and more. The goal of the 50-State Simulation Project is to enable researchers, practitioners, and the general public to use cutting-edge redistricting simulation analysis to evaluate enacted co... | Provide a detailed description of the following dataset: 50stateSimulations |
Replication Data for: The use of differential privacy for census data and its impact on redistricting | Census statistics play a key role in public policy decisions and social science research. However, given the risk of revealing individual information, many statistical agencies are considering disclosure control methods based on differential privacy, which add noise to tabulated data. Unlike other applications of diffe... | Provide a detailed description of the following dataset: Replication Data for: The use of differential privacy for census data and its impact on redistricting |
PointCloud-C | PointCloud-C is the very first test-suite for point cloud robustness analysis under corruptions.
- Two sets: ModelNet-C for point cloud classification and ShapeNet-C for part segmentation.
- Real-world corruption sources, ranging from object-, senor-, and processing-levels.
- Seven types of corruptions, each with ... | Provide a detailed description of the following dataset: PointCloud-C |
PDDL Generators | This repository is a collection of PDDL generators, some of which have been used to generate benchmarks for the International Planning Competition (IPC). | Provide a detailed description of the following dataset: PDDL Generators |
larousse_1905_wd | This dataset links all the entries describing named entities of _Petit Larousse illustré_, a French dictionary published in 1905, to wikidata identifiers. The dataset is available in the JSON format as a list of entries, where each entry is a dictionary with two keys: the text of the entry and the list of wikidata iden... | Provide a detailed description of the following dataset: larousse_1905_wd |
ISIC 2019 | The goal for ISIC 2019 is classify dermoscopic images among nine different diagnostic categories.25,331 images are available for training across 8 different categories. Two tasks will be available for participation: 1) classify dermoscopic images without meta-data,
and 2) classify images with additional available meta... | Provide a detailed description of the following dataset: ISIC 2019 |
Brain Tumor MRI Dataset | This dataset is a combination of the following three datasets :
figshare,
SARTAJ dataset and
Br35H
This dataset contains 7022 images of human brain MRI images which are classified into 4 classes: glioma - meningioma - no tumor and pituitary. | Provide a detailed description of the following dataset: Brain Tumor MRI Dataset |
DCASE 2021 TASK1A | DCASE 2021 TASK1A dataset consists of audio examples from 10 different audio scenes. For more detailed, please follow the link: https://dcase.community/challenge2021/task-acoustic-scene-classification | Provide a detailed description of the following dataset: DCASE 2021 TASK1A |
Replication Data for: Singapore Soundscape Site Selection Survey (S5) | This dataset contains the data used for all statistical analysis in our publication "Singapore Soundscape Site Selection Survey (S5): Identification of Characteristic Soundscapes of Singapore via Weighted k-means Clustering", summarised in a single .csv file.
For more details on the study methodology, please refer t... | Provide a detailed description of the following dataset: Replication Data for: Singapore Soundscape Site Selection Survey (S5) |
ConcurrentQA Benchmark | ConcurrentQA is a textual multi-hop QA benchmark to require concurrent retrieval over multiple data-distributions (i.e. Wikipedia and email data). The dataset follow the exact same schema and design as HotpotQA. The data set is downloadable here: https://github.com/facebookresearch/concurrentqa. It also contains model ... | Provide a detailed description of the following dataset: ConcurrentQA Benchmark |
RICH | Inferring human-scene contact (HSC) is the first step toward understanding how humans interact with their surroundings. While detecting 2D human-object interaction (HOI) and reconstructing 3D human pose and shape (HPS) have enjoyed significant progress, reasoning about 3D human-scene contact from a single image is stil... | Provide a detailed description of the following dataset: RICH |
Click-Through Rate Prediction - Avazu | # File descriptions
* train - Training set. 10 days of click-through data, ordered chronologically. Non-clicks and clicks are subsampled according to different strategies.
* test - Test set. 1 day of ads to for testing your model predictions.
* sampleSubmission.csv - Sample submission file in the correct format, ... | Provide a detailed description of the following dataset: Click-Through Rate Prediction - Avazu |
Deep Indices | This dataset inclue multi-spectral acquisition of vegetation for the conception of new DeepIndices. The images were acquired with the Airphen (Hyphen, Avignon, France) six-band multi-spectral camera configured using the 450/570/675/710/730/850 nm bands with a 10 nm FWHM. The dataset were acquired on the site of INRAe i... | Provide a detailed description of the following dataset: Deep Indices |
Multi-Spectral Leaf Segmentation | This dataset were acquired with the Airphen (Hyphen, Avignon, France) six-band multi-spectral camera configured using the 450/570/675/710/730/850 nm bands with a 10 nm FWHM. And acquired on the site of INRAe in Montoldre (Allier, France, at 46°20'30.3"N 3°26'03.6"E) within the framework of the “RoSE challenge” founded ... | Provide a detailed description of the following dataset: Multi-Spectral Leaf Segmentation |
NovelCraft | Scene-focused, multi-modal, episodic data of the images and symbolic world-states seen
by an agent completing a pogo-stick assembly task within a video game world. Classes consist of
episodes with novel objects inserted. A subset of these novel objects can impact gameplay and agent behavior. Novelty objects can vary ... | Provide a detailed description of the following dataset: NovelCraft |
ArtBench-10 (32x32) | We introduce ArtBench-10, the first class-balanced, high-quality, cleanly annotated, and standardized dataset for benchmarking artwork generation. It comprises 60,000 images of artwork from 10 distinctive artistic styles, with 5,000 training images and 1,000 testing images per style. ArtBench-10 has several advantages ... | Provide a detailed description of the following dataset: ArtBench-10 (32x32) |
BindingDB | BindingDB is a public, web-accessible database of measured binding affinities, focusing chiefly on the interactions of protein considered to be drug-targets with small, drug-like molecules. As of May 27, 2022, BindingDB contains 41,296 Entries, each with a DOI, containing 2,519,702 binding data for 8,810 protein target... | Provide a detailed description of the following dataset: BindingDB |
LIT-PCBA(ALDH1) | Comparative evaluation of virtual screening methods requires a rigorous benchmarking procedure on diverse, realistic, and unbiased data sets. Recent investigations from numerous research groups unambiguously demonstrate that artificially constructed ligand sets classically used by the community (e.g., DUD, DUD-E, MUV) ... | Provide a detailed description of the following dataset: LIT-PCBA(ALDH1) |
LIT-PCBA(ESR1_ant) | Comparative evaluation of virtual screening methods requires a rigorous benchmarking procedure on diverse, realistic, and unbiased data sets. Recent investigations from numerous research groups unambiguously demonstrate that artificially constructed ligand sets classically used by the community (e.g., DUD, DUD-E, MUV) ... | Provide a detailed description of the following dataset: LIT-PCBA(ESR1_ant) |
LIT-PCBA(KAT2A) | Comparative evaluation of virtual screening methods requires a rigorous benchmarking procedure on diverse, realistic, and unbiased data sets. Recent investigations from numerous research groups unambiguously demonstrate that artificially constructed ligand sets classically used by the community (e.g., DUD, DUD-E, MUV) ... | Provide a detailed description of the following dataset: LIT-PCBA(KAT2A) |
LIT-PCBA(MAPK1) | Comparative evaluation of virtual screening methods requires a rigorous benchmarking procedure on diverse, realistic, and unbiased data sets. Recent investigations from numerous research groups unambiguously demonstrate that artificially constructed ligand sets classically used by the community (e.g., DUD, DUD-E, MUV) ... | Provide a detailed description of the following dataset: LIT-PCBA(MAPK1) |
ESOL(scaffold) | MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previousl... | Provide a detailed description of the following dataset: ESOL(scaffold) |
Lipophilicity(scaffold) | MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previousl... | Provide a detailed description of the following dataset: Lipophilicity(scaffold) |
FreeSolv(scaffold) | MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previousl... | Provide a detailed description of the following dataset: FreeSolv(scaffold) |
BACE(scaffold) | MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previousl... | Provide a detailed description of the following dataset: BACE(scaffold) |
BBBP(scaffold) | MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previousl... | Provide a detailed description of the following dataset: BBBP(scaffold) |
SIDER(scaffold) | MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previousl... | Provide a detailed description of the following dataset: SIDER(scaffold) |
Tox21(scaffold) | MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previousl... | Provide a detailed description of the following dataset: Tox21(scaffold) |
ToxCast(scaffold) | MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previousl... | Provide a detailed description of the following dataset: ToxCast(scaffold) |
VizNet-Sato | VizNet-Sato is a dataset from the authors of Sato and is based on the VizNet dataset. The authors choose from VizNet only relational web tables with headers matching their selected 78 DBpedia semantic types. The selected tables are divided into two categories: Full tables and Multi-column only tables. The first catego... | Provide a detailed description of the following dataset: VizNet-Sato |
Road Anomaly | This dataset contains images of unusual dangers which can be encountered by a vehicle on the road – animals, rocks, traffic cones and other obstacles. Its purpose is testing autonomous driving perception algorithms in rare but safety-critical circumstances. | Provide a detailed description of the following dataset: Road Anomaly |
BBC News Summary | This dataset was created using a dataset used for data categorization that onsists of 2225 documents from the BBC news website corresponding to stories in five topical areas from 2004-2005 used in the paper of D. Greene and P. Cunningham. "Practical Solutions to the Problem of Diagonal Dominance in Kernel Document Clus... | Provide a detailed description of the following dataset: BBC News Summary |
Bengali.AI Handwritten Graphemes | This dataset contains images of individual hand-written Bengali characters. Bengali characters (graphemes) are written by combining three components: a grapheme_root, vowel_diacritic, and consonant_diacritic. Your challenge is to classify the components of the grapheme in each image. There are roughly 10,000 possible g... | Provide a detailed description of the following dataset: Bengali.AI Handwritten Graphemes |
RSTPReid | RSTPReid contains 20505 images of 4,101 persons from 15 cameras. Each person has 5 corresponding images taken by different cameras with complex both indoor and outdoor scene transformations and backgrounds in various periods of time, which makes RSTPReid much more challenging and more adaptable to real scenarios. Each ... | Provide a detailed description of the following dataset: RSTPReid |
IBISCape | A Simulated Benchmark for multi-modal SLAM Systems Evaluation in Large-scale Dynamic Environments. | Provide a detailed description of the following dataset: IBISCape |
Active TLS Stack Fingerprinting Measurement Data | Measurement data related to the publication „Active TLS Stack Fingerprinting: Characterizing TLS Server Deployments at Scale“. It contains weekly TLS and HTTP scan data and the TLS fingerprints for each target. | Provide a detailed description of the following dataset: Active TLS Stack Fingerprinting Measurement Data |
DME VQA dataset | Medical VQA dataset built from the [IDRiD](https://ieee-dataport.org/open-access/indian-diabetic-retinopathy-image-dataset-idrid) and [eOphta](https://www.adcis.net/en/third-party/e-ophtha/) datasets. The dataset contains both healthy and unhealthy fundus images. For each image, a set of pre-defined questions is gener... | Provide a detailed description of the following dataset: DME VQA dataset |
4D-OR | 4D-OR includes a total of 6734 scenes, recorded by six calibrated RGB-D Kinect sensors 1 mounted to the ceiling of the OR, with one frame-per-second, providing synchronized RGB and depth images. We provide fused point cloud sequences of entire scenes, automatically annotated human 6D poses and 3D bounding boxes for OR ... | Provide a detailed description of the following dataset: 4D-OR |
YouTube-VIS 2021 | 3,859 high-resolution YouTube videos, 2,985 training videos, 421 validation videos and 453 test videos.
An improved 40-category label set by merging eagle and owl into bird, ape into monkey, deleting hands, and adding flying disc, squirrel and whale
8,171 unique video instances
232k high-quality manual annotations | Provide a detailed description of the following dataset: YouTube-VIS 2021 |
T2Dv2 | The T2Dv2 dataset consists of 779 tables originating from the English-language subset of the [WebTables](http://webdatacommons.org/webtables/) corpus. 237 tables are annotated for the Table Type Detection task, 236 for the Columns Property Annotation (CPA) task and 235 for the Row Annotation task. The annotations that ... | Provide a detailed description of the following dataset: T2Dv2 |
Chalearn-AutoML-1 | This meta-dataset is first used in the AutoML1 challenge organized by Chalearn in 2015. It is composed of 30 pre-processed datasets, chosen to illustrate a wide variety of domains of applications: biology and medicine, ecology, energy and
sustainability management, image, text, audio, speech, video and other sensor da... | Provide a detailed description of the following dataset: Chalearn-AutoML-1 |
NumtaDB | To benchmark Bengali digit recognition algorithms, a large publicly available dataset is required which is free from biases originating from geographical location, gender, and age. With this aim in mind, NumtaDB, a dataset consisting of more than 85,000 images of hand-written Bengali digits, has been assembled. | Provide a detailed description of the following dataset: NumtaDB |
OpenXAI | OpenXAI is the first general-purpose lightweight library that provides a comprehensive list of functions to systematically evaluate the quality of explanations generated by attribute-based explanation methods. OpenXAI supports the development of new datasets (both synthetic and real-world) and explanation methods, with... | Provide a detailed description of the following dataset: OpenXAI |
HumanML3D | HumanML3D is a 3D human motion-language dataset that originates from a combination of HumanAct12 and Amass dataset. It covers a broad range of human actions such as daily activities (e.g., 'walking', 'jumping'), sports (e.g., 'swimming', 'playing golf'), acrobatics (e.g., 'cartwheel') and artistry (e.g., 'dancing'). Ov... | Provide a detailed description of the following dataset: HumanML3D |
Persistence Diagram Benchmark | Persistence Diagram Benchmark | Provide a detailed description of the following dataset: Persistence Diagram Benchmark |
WikipediaGS | The WikipediaGS dataset was created by extracting Wikipedia tables from Wikipedia pages. It consists of 485,096 tables which were annotated with DBpedia entities for the Cell Entity Annotation (CEA) task.
Additionally, a subset of these tables was annotated by [Chen et al.](https://paperswithcode.com/paper/190600781... | Provide a detailed description of the following dataset: WikipediaGS |
CoNLL 2017 Shared Task - Automatically Annotated Raw Texts and Word Embeddings | Automatic segmentation, tokenization and morphological and syntactic annotations of raw texts in 45 languages, generated by UDPipe (http://ufal.mff.cuni.cz/udpipe), together with word embeddings of dimension 100 computed from lowercased texts by word2vec (https://code.google.com/archive/p/word2vec/). | Provide a detailed description of the following dataset: CoNLL 2017 Shared Task - Automatically Annotated Raw Texts and Word Embeddings |
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