dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
ChineseLP | The ChineseLP dataset contains 411 vehicle images (mostly of passenger cars) with Chinese license plates (LPs). It consists of 252 images captured by the authors and 159 images
downloaded from the internet. The images present great variations in resolution (from 143 × 107 to 2048 × 1536 pixels), illumination and backg... | Provide a detailed description of the following dataset: ChineseLP |
UFPR-ADMR-v1 | This dataset contains 2,000 dial meter images obtained on-site by employees of the Energy Company of Paraná (Copel), which serves more than 4 million consuming units in the Brazilian state of Paraná. The images were acquired with many different cameras and are available in the JPG format with 320×640 or 640×320 pixels ... | Provide a detailed description of the following dataset: UFPR-ADMR-v1 |
LFM-BeyMS | This dataset is based on the LFM-1b [ and the Cultural LFM-1b [2] datasets. LFM-BeyMS includes equally-sized groups of both, beyond-mainstream and mainstream music listeners and thus, can be used for studying the characteristics of beyond-mainstream music listeners for recommendation experiments. For more details, we r... | Provide a detailed description of the following dataset: LFM-BeyMS |
GUITAR-FX-DIST: A Dataset of Processed Guitar Recordings for Music Research - (Mono Continuous) | GUITAR-FX-DIST is a dataset of electric guitar recordings processed with overdrive, distortion, and fuzz audio effects. It was developed for research in guitar effects detection, classification, and parameters estimation. The dataset is also useful for research on automatic music transcription, intelligent music produc... | Provide a detailed description of the following dataset: GUITAR-FX-DIST: A Dataset of Processed Guitar Recordings for Music Research - (Mono Continuous) |
GUITAR-FX-DIST: A Dataset of Processed Guitar Recordings for Music Research - (Mono Discrete) | GUITAR-FX-DIST is a dataset of electric guitar recordings processed with overdrive, distortion and fuzz audio effects. It was developed for research in guitar effects detection, classification and parameters estimation. The dataset is also useful for research on automatic music transcription, intelligent music producti... | Provide a detailed description of the following dataset: GUITAR-FX-DIST: A Dataset of Processed Guitar Recordings for Music Research - (Mono Discrete) |
GUITAR-FX-DIST: A Dataset of Processed Guitar Recordings for Music Research - (Poly Discrete) | GUITAR-FX-DIST is a dataset of electric guitar recordings processed with overdrive, distortion and fuzz audio effects. It was developed for research in guitar effects detection, classification and parameters estimation. The dataset is also useful for research on automatic music transcription, intelligent music producti... | Provide a detailed description of the following dataset: GUITAR-FX-DIST: A Dataset of Processed Guitar Recordings for Music Research - (Poly Discrete) |
GUITAR-FX-DIST: A Dataset of Processed Guitar Recordings for Music Research - (Poly Continuous) | GUITAR-FX-DIST is a dataset of electric guitar recordings processed with overdrive, distortion and fuzz audio effects. It was developed for research in guitar effects detection, classification and parameters estimation. The dataset is also useful for research on automatic music transcription, intelligent music producti... | Provide a detailed description of the following dataset: GUITAR-FX-DIST: A Dataset of Processed Guitar Recordings for Music Research - (Poly Continuous) |
METAR | Weather reports of 57 stations in the east coast. | Provide a detailed description of the following dataset: METAR |
Netzschleuder | This is a catalogue and repository of network datasets with the aim of aiding scientific research.
This website is meant to be browsed both by humans and machines alike, and can also be accessed via a convenient JSON API, or via the [graph-tool](https://graph-tool.skewed.de/static/doc/collection.html#graph_tool.coll... | Provide a detailed description of the following dataset: Netzschleuder |
Darpa OpTC | Operationally Transparent Cyber (OpTC) was a technology transition pilot study funded under Boston Fusion Corp.'s Cyber APT Scenarios for Enterprise Systems (CASES) project. Its primary objective was to determine if DARPA Transparent Computing (TC) program technologies could scale without loss of detection performance ... | Provide a detailed description of the following dataset: Darpa OpTC |
Home Action Genome | Home Action Genome is a large-scale multi-view video database of indoor daily activities. Every activity is captured by synchronized multi-view cameras, including an egocentric view.
There are 30 hours of vides with 70 classes of daily activities and 453 classes of atomic actions. | Provide a detailed description of the following dataset: Home Action Genome |
OVIS | OVIS is a new large scale benchmark dataset for video instance segmentation task. It is designed with the philosophy of perceiving object occlusions in videos, which could reveal the complexity and the diversity of real-world scenes. OVIS consists of:
* 296k high-quality instance masks
* 25 commonly seen semantic c... | Provide a detailed description of the following dataset: OVIS |
SyntheticFur | **SyntheticFur** is a dataset for neural rendering. Collecting and generating high quality fur images is an expensive and difficult process that requires content specialists to generate. By releasing this unique dataset with high quality lighting simulation via ray tracing, this can save time for researchers seeking to... | Provide a detailed description of the following dataset: SyntheticFur |
TabLeX | **TabLeX** is a large-scale benchmark dataset comprising table images generated from scientific articles. TabLeX consists of two subsets, one for table structure extraction and the other for table content extraction. Each table image is accompanied by its corresponding LATEX source code. To facilitate the development o... | Provide a detailed description of the following dataset: TabLeX |
PeMSD7 | PeMSD7 is traffic data in District 7 of California consisting of the traffic speed of 228 sensors while the period is from May to June in 2012 (only weekdays) with a time interval of 5 minutes. This dataset is popular for benchmark the traffic forecasting models. | Provide a detailed description of the following dataset: PeMSD7 |
PeMSD4 | The dataset refers to the traffic speed data in San Francisco Bay Area, containing 307 sensors on 29 roads. The time span of the dataset is January-February in 2018. It is a popular benchmark for traffic forecasting. | Provide a detailed description of the following dataset: PeMSD4 |
PeMSD8 | This dataset contains the traffic data in San Bernardino from July to August in 2016, with 170 detectors on 8 roads with a time interval of 5 minutes. This dataset is popular as a benchmark traffic forecasting dataset. | Provide a detailed description of the following dataset: PeMSD8 |
SaRoCo | **SaRoCo** is a dataset for detecting satire in Romanian news containing 55,608 news articles from multiple real and satirical news sources, of which 27,980 are regular and 27,628 satirical news reports. We provide the data in csv format, in three files following the train/validation/test splits. | Provide a detailed description of the following dataset: SaRoCo |
CHAOS | CHAOS challenge aims the segmentation of abdominal organs (liver, kidneys and spleen) from CT and MRI data. ONsite section of the CHAOS was held in The IEEE International Symposium on Biomedical Imaging (ISBI) on April 11, 2019, Venice, ITALY. Online submissions are still welcome!
\textbf{Challenge Description}
... | Provide a detailed description of the following dataset: CHAOS |
TrackML challenge Throughput phase dataset | The dataset comprises multiple independent events, where each event contains simulated measurements (essentially 3D points) of particles generated in a collision between proton bunches at the Large Hadron Collider at CERN. The goal of the tracking machine learning challenge is to group the recorded measurements or hit ... | Provide a detailed description of the following dataset: TrackML challenge Throughput phase dataset |
Scroll Readability Dataset | Scroll Readability Dataset contains scroll interactions of 598 participants reading advanced and elementary texts from the OneStopEnglish corpus. | Provide a detailed description of the following dataset: Scroll Readability Dataset |
AID | AID is a new large-scale aerial image dataset, by collecting sample images from Google Earth imagery. Note that although the Google Earth images are post-processed using RGB renderings from the original optical aerial images, it has proven that there is no significant difference between the Google Earth images with the... | Provide a detailed description of the following dataset: AID |
GID | Gaofen Image Dataset (GID) is a large-scale land-cover dataset constructed with Gaofen-2 (GF-2) satellite images. This dataset has superiorities over the existing land-cover dataset because of its large coverage, wide distribution, and high spatial resolution. It contains 150 GF-2 images annotated at the pixel level fo... | Provide a detailed description of the following dataset: GID |
WHU-RS19 | WHU-RS19 is a set of satellite images exported from Google Earth, which provides high-resolution satellite images up to 0.5 m. Some samples of the database are displayed in the following picture. It contains 19 classes of meaningful scenes in high-resolution satellite imagery, including airport, beach, bridge, commerci... | Provide a detailed description of the following dataset: WHU-RS19 |
SECOND | SECOND is a well-annotated semantic change detection dataset. To ensure data diversity, we firstly collect 4662 pairs of aerial images from several platforms and sensors. These pairs of images are distributed over the cities such as Hangzhou, Chengdu, and Shanghai. Each image has size 512 x 512 and is annotated at the ... | Provide a detailed description of the following dataset: SECOND |
Shellcode_IA32 | Shellcode_IA32 is a dataset containing 20 years of shellcodes from a variety of sources is the largest collection of shellcodes in assembly available to date.
This dataset consists of 3,200 examples of instructions in assembly language for IA-32 (the 32-bit version of the x86 Intel Architecture) from publicly availa... | Provide a detailed description of the following dataset: Shellcode_IA32 |
SILICONE Benchmark | The Sequence labellIng evaLuatIon benChmark fOr spoken laNguagE (SILICONE) benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems specifically designed for spoken language. All datasets are in the English language and covers a large variety of domains (e.g... | Provide a detailed description of the following dataset: SILICONE Benchmark |
FKD | The football keyword dataset (FKD), as a new keyword spotting dataset in Persian, is collected with crowdsourcing. This dataset contains nearly 31000 samples in 18 classes. | Provide a detailed description of the following dataset: FKD |
SDCNL (Suicide vs Depression Classification) | We develop a primary dataset based on our task of suicide or depression classification. This dataset is web-scraped from Reddit. We collect our data from subreddits using the Python Reddit API. We specifically scrape from two subreddits, r/SuicideWatch3 and r/Depression. The dataset contains 1,895 total posts. We utili... | Provide a detailed description of the following dataset: SDCNL (Suicide vs Depression Classification) |
Reddit C-SSRS | The C-SSRS dataset contains 500 Reddit posts from the subreddit r/depression. These posts are labeled by psychologists on a five point scale according to guidelines established in the Columbia Suicide Severity Rating Scale, which progress according to
severity of depression. As this dataset is clinically verified and ... | Provide a detailed description of the following dataset: Reddit C-SSRS |
SHHS | The Sleep Heart Health Study (SHHS) is a multi-center cohort study implemented by the National Heart Lung & Blood Institute to determine the cardiovascular and other consequences of sleep-disordered breathing. It tests whether sleep-related breathing is associated with an increased risk of coronary heart disease, strok... | Provide a detailed description of the following dataset: SHHS |
AraCOVID19-MFH | AraCOVID19-MFH is a manually annotated multi-label Arabic COVID-19 fake news and hate speech detection dataset. The dataset contains 10,828 Arabic tweets annotated with 10 different labels. | Provide a detailed description of the following dataset: AraCOVID19-MFH |
UAVVaste | The UAVVaste dataset consists to date of 772 images and 3716 annotations. The main motivation for creation of the dataset was the lack of domain-specific data. The datasets that are widely used for object detection evaluation benchmarking. The dataset is made publicly available and is intended to be expanded.
| **... | Provide a detailed description of the following dataset: UAVVaste |
AvaSym | Global Symmetry Ground-truth for AVA dataset.
Release Date: 2016.
Users of this software are encouraged to cite the following article:
Elawady, Mohamed, Cécile Barat, Christophe Ducottet, and Philippe Colantoni. "Global Bilateral Symmetry Detection Using Multiscale Mirror Histograms." In International Conference... | Provide a detailed description of the following dataset: AvaSym |
ConvQuestions | ConvQuestions is the first realistic benchmark for conversational question answering over knowledge graphs. It contains 11,200 conversations which can be evaluated over Wikidata. They are compiled from the inputs of 70 Master crowdworkers on Amazon Mechanical Turk, with conversations from five domains: Books, Movies, S... | Provide a detailed description of the following dataset: ConvQuestions |
Drinking Waste Classification | ## About the Dataset:
4 classes of drinking waste: Aluminium Cans, Glass bottles, PET (plastic) bottles and HDPE (plastic) Milk bottles.
rawimgs - images of 4 classes of waste
YOLO_imgs - images of 4 classes of waste with corresponding txt file (annotations for YOLO framework)
labels.txt - labels of the classes
... | Provide a detailed description of the following dataset: Drinking Waste Classification |
R2VQ | R2VQ is a dataset designed for testing competence-based comprehension of machines over a multimodal recipe collection, which contains text-video aligned recipes.
A total of 51,331 cooking events are annotated, which contain 19,201 explicit ingredients, 16,338 implicit ingredients, 12,316 explicit props, and 11,868 i... | Provide a detailed description of the following dataset: R2VQ |
ionosphere | The original ionosphere dataset from UCI machine learning repository is a binary classification dataset with dimensionality 34. There is one attribute having values all zeros, which is discarded. So the total number of dimensions are 33. The ‘bad’ class is considered as outliers class and the ‘good’ class as inliers. | Provide a detailed description of the following dataset: ionosphere |
GeoLifeCLEF 2020 | The GeoLifeCLEF 2020 dataset is a large-scale remote sensing dataset. More specifically, it consists of 1.9 million species observations from the community science platform iNaturalist, each of which is paired with high-resolution covariates (RGB-IR imagery, land cover, and altitude). The dataset is roughly evenly spli... | Provide a detailed description of the following dataset: GeoLifeCLEF 2020 |
DBATES | DBATES is a database of multimodal communication features extracted from debate speeches in the 2019 North American Universities Debate Championships (NAUDC).
**Author's note:** If you want to access the dataset for research purposes, please email the authors.
Image source: [https://arxiv.org/pdf/2103.14189v1.pdf... | Provide a detailed description of the following dataset: DBATES |
Boombox | **Boombox** is a multi-modal dataset for visual reconstruction from acoustic vibrations. Involves dropping objects into a box and capturing resulting images and vibrations. Used for training ML systems that predict images from vibration.
**Potential application domain:** Computer Vision, Multimodal Perception, Visio... | Provide a detailed description of the following dataset: Boombox |
ARC-100 | The **ARC-100** dataset was collected as part of a prototype retail checkout system titled ARC (Automatic Retail Checkout). It consists of 31,000 $640\times480$ RGB images of 100 commonly found retail items in Lahore, Pakistan. Each retail item has 310 images captured at various *logical* orientations (on a black, matt... | Provide a detailed description of the following dataset: ARC-100 |
ImageNet-O | ImageNet-O consists of images from classes that are not found in the ImageNet-1k dataset. It is used to test the robustness of vision models to out-of-distribution samples. It's reported using the AUPR metric. | Provide a detailed description of the following dataset: ImageNet-O |
ImageNet-9 | ImageNet-9 consists of images with different amounts of background and foreground signal, which you can use to measure the extent to which your models rely on image backgrounds. This dataset is helpful in testing the robustness of vision models with respect to their dependence on the backgrounds of images. | Provide a detailed description of the following dataset: ImageNet-9 |
xSID | xSID, a new evaluation benchmark for cross-lingual (X) Slot and Intent Detection in 13 languages from 6 language families, including a very low-resource dialect, covering Arabic (ar), Chinese (zh), Danish (da), Dutch (nl), English (en), German (de), Indonesian (id), Italian (it), Japanese (ja), Kazakh (kk), Serbian (s... | Provide a detailed description of the following dataset: xSID |
Few-NERD | Few-NERD is a large-scale, fine-grained manually annotated named entity recognition dataset, which contains 8 coarse-grained types, 66 fine-grained types, 188,200 sentences, 491,711 entities, and 4,601,223 tokens. Three benchmark tasks are built, one is supervised (Few-NERD (SUP)) and the other two are few-shot (Few-NE... | Provide a detailed description of the following dataset: Few-NERD |
DL-HARD | Deep Learning Hard (**DL-HARD**) is an annotated dataset designed to more effectively evaluate neural ranking models on complex topics. It builds on TREC Deep Learning (DL) questions extensively annotated with query intent categories, answer types, wikified entities, topic categories, and result type metadata from a l... | Provide a detailed description of the following dataset: DL-HARD |
SciDuet | **SciDuet** is a dataset for training and benchmarking models for automating document-to-slides generation. It consists of pairs of papers and their corresponding slides decks from recent years' NLP and ML conferences (e.g., ACL). This dataset contains 1,088 papers and 10,034 slides. | Provide a detailed description of the following dataset: SciDuet |
Flat Real World Simulink Models | This dataset contains:
(1) Slforge Generated Simulink Models : Synthetic Simulink Models
(2) Source of Real World Simulink Models
The `.txt` file is a combined text file that contains all the real world Simulink models based on SLGPT's experimental setup. | Provide a detailed description of the following dataset: Flat Real World Simulink Models |
PhotoShape | The PhotoShape dataset consists of photorealistic, relightable, 3D shapes produced by the work proposed in the work of [Park et al. (2021)](https://paperswithcode.com/paper/photoshape-photorealistic-materials-for-large). | Provide a detailed description of the following dataset: PhotoShape |
Fruits 360 | ## Fruits 360 dataset: A dataset of images containing fruits and vegetables
## Version: 2020.05.18.0
### Content
The following fruits and are included:
Apples (different varieties: Crimson Snow, Golden, Golden-Red, Granny Smith, Pink Lady, Red, Red Delicious), Apricot, Avocado, Avocado ripe, Banana (Yellow, ... | Provide a detailed description of the following dataset: Fruits 360 |
WMT 2021 Ge'ez-Amharic | **WMT 2021 Ge'ez-Amharic** is a Ge'ez-Amharic dataset prepared for NMT tasks of the 6th Workshop on NLP at Debre Berhan University, Ethiopia. The corpus has been collected from:
* Ethiopian Orthodox Church old bible (from ethiopianorthodox.org), Anaphora, praise of St. Virgin Mary, praise of Lord Jesus and other Ch... | Provide a detailed description of the following dataset: WMT 2021 Ge'ez-Amharic |
PubMed Term, Abstract, Conclusion, Title Dataset | This dataset gathers three types of pairs: Title-to-Abstract (Training: 22,811/Development: 2095/Test: 2095), Abstract-to-Conclusion and Future work (Training: 22,811/Development: 2095/Test: 2095), Conclusion and Future work-to-Title (Training: 15,902/Development: 2095/Test: 2095) from PubMed. Each pair contains a pair... | Provide a detailed description of the following dataset: PubMed Term, Abstract, Conclusion, Title Dataset |
PubMed Paper Reading Dataset | This dataset gathers 14,857 entities, 133 relations, and entities corresponding tokenized text from PubMed. It contains 875,698 training pairs, 109,462 development pairs, and 109,462 test pairs. | Provide a detailed description of the following dataset: PubMed Paper Reading Dataset |
ReviewRobot Dataset | # ReviewRobot Dataset
## Overview
This repository contains data for paper ReviewRobot: Explainable Paper Review Generation based on Knowledge Synthesis. [[Dataset]](https://drive.google.com/file/d/1NclEwGEVcHCrSWk8s3lDjvEbMlWXQoXM/view?usp=sharing)
## Dataset
There are three folders: `Raw_data`, `IE_result`, an... | Provide a detailed description of the following dataset: ReviewRobot Dataset |
FlyingThings3D | **FlyingThings3D** is a synthetic dataset for optical flow, disparity and scene flow estimation. It consists of everyday objects flying along randomized 3D trajectories. We generated about 25,000 stereo frames with ground truth data. Instead of focusing on a particular task (like KITTI) or enforcing strict naturalism ... | Provide a detailed description of the following dataset: FlyingThings3D |
ATD-12K | **ATD-12K** is a large-scale animation triplet dataset, which comprises 12,000 triplets(train10k,test2k) by manually inspect and the test2k with rich annotations, including levels of difficulty, the Regions of Interest (RoIs) on movements, and tags on motion categories
The dataset collected from 30 series of movies(... | Provide a detailed description of the following dataset: ATD-12K |
Project CodeNet | **Project CodeNet** is a large-scale dataset with approximately 14 million code samples, each of which is an intended solution to one of 4000 coding problems. The code samples are written in over 50 programming languages (although the dominant languages are C++, C, Python, and Java) and they are annotated with a rich s... | Provide a detailed description of the following dataset: Project CodeNet |
DanbooRegion | **DanbooRegion** is a dataset consists of 5377 in-the-wild illustration downloaded from the Danbooru2018 and region segment map annotation pairs
samples are provided as at 1024px 8-bit RGB images, and region segment maps as int-32 index images. | Provide a detailed description of the following dataset: DanbooRegion |
Voice Navigation | **Voice Navigation** is a large-scale dataset of Chinese speech for slot filling, containing more than 830,000 samples. | Provide a detailed description of the following dataset: Voice Navigation |
Active Terahertz | This is a public dataset for evaluating multi-object detection algorithms in active Terahertz imaging resolution 5 mm by 5 mm. | Provide a detailed description of the following dataset: Active Terahertz |
BookSum | **BookSum** is a collection of datasets for long-form narrative summarization. This dataset covers source documents from the literature domain, such as novels, plays and stories, and includes highly abstractive, human written summaries on three levels of granularity of increasing difficulty: paragraph-, chapter-, and b... | Provide a detailed description of the following dataset: BookSum |
SPI dataset | The **SPI dataset** consists of force-controlled industrial robot data for training shadow program inversion (SPI) models. | Provide a detailed description of the following dataset: SPI dataset |
QAConv | **QAConv** is a new question answering (QA) dataset that uses conversations as a knowledge source. We focus on informative conversations including business emails, panel discussions, and work channels. Unlike opendomain and task-oriented dialogues, these conversations are usually long, complex, asynchronous, and involv... | Provide a detailed description of the following dataset: QAConv |
Fetoscopy Placenta Data | The fetoscopy placenta dataset is associated with our MICCAI2020 publication titled [“Deep Placental Vessel Segmentation for Fetoscopic Mosaicking”](https://arxiv.org/pdf/2007.04349.pdf). The dataset contains 483 frames with ground-truth vessel segmentation annotations taken from six different in vivo fetoscopic proced... | Provide a detailed description of the following dataset: Fetoscopy Placenta Data |
Fusion-DHL | Fusion-DHL is a multimodal sensor dataset with ground-truth positions. | Provide a detailed description of the following dataset: Fusion-DHL |
seeds | The examined group comprised kernels belonging to three different varieties of wheat: Kama, Rosa and Canadian, 70 elements each, randomly selected for the experiment. High quality visualization of the internal kernel structure was detected using a soft X-ray technique. It is non-destructive and considerably cheaper tha... | Provide a detailed description of the following dataset: seeds |
97 synthetic datasets | 97 synthetic datasets consists of 97 datasets (as illustrated in the figure) and can be used to test graph-based clustering algorithms.
https://github.com/deric/clustering-benchmark | Provide a detailed description of the following dataset: 97 synthetic datasets |
PPR10K | **PPR10K** is a dataset for portrait photo retouching (PPR), which aims to enhance the visual quality of a collection of flat-looking portrait photos. The Portrait Photo Retouching dataset (PPR10K) is a large-scale and diverse dataset that contains:
* 11,161 high-quality raw portrait photos (resolutions from 4K to 8... | Provide a detailed description of the following dataset: PPR10K |
SoftAttributes | The dataset consists of sets of movie titles, with each set annotated with a single English soft attribute (subjective descriptive property, such as 'confusing' or 'romantic') and a reference movie. For each set, a crowd worker has placed the movies into three sets: more, equally, and less than the reference movie. The... | Provide a detailed description of the following dataset: SoftAttributes |
Ali-CCP | This data set is provided by Alimama | Provide a detailed description of the following dataset: Ali-CCP |
Essay-BR | This repository contains essays written by high school Brazilian students. These essays were graded by humans professionals following the criteria of the ENEM exam. | Provide a detailed description of the following dataset: Essay-BR |
OpenMEVA | OpenMEVA is a benchmark for evaluating open-ended story generation metrics. OpenMEVA provides a comprehensive test suite to assess the capabilities of metrics, including (a) the correlation with human judgments, (b) the generalization to different model outputs and datasets, (c) the ability to judge story coherence, an... | Provide a detailed description of the following dataset: OpenMEVA |
RITEyes | Deep neural networks for video based eye tracking have demonstrated resilience to noisy environments, stray reflections and low resolution. However, to train these networks, a large number of manually annotated images are required. To alleviate the cumbersome process of manual labeling, computer graphics rendering is e... | Provide a detailed description of the following dataset: RITEyes |
NAVER LABS Localization Datasets | The NAVER LABS localization datasets are 5 new indoor datasets for visual localization in challenging real-world environments. They were captured in a large shopping mall and a large metro station in Seoul, South Korea, using a dedicated mapping platform consisting of 10 cameras and 2 laser scanners. In order to obtain... | Provide a detailed description of the following dataset: NAVER LABS Localization Datasets |
MIT-Adobe FiveK | The **MIT-Adobe FiveK** dataset consists of 5,000 photographs taken with SLR cameras by a set of different photographers. They are all in RAW format; that is, all the information recorded by the camera sensor is preserved. We made sure that these photographs cover a broad range of scenes, subjects, and lighting conditi... | Provide a detailed description of the following dataset: MIT-Adobe FiveK |
behavioral observation data entry apps | In this repository, we provide the set-up files and output files of 5 behavioral observation data entry applications. These applications allow observers to collect animal behavior data on a handheld computer (phone/tablet). | Provide a detailed description of the following dataset: behavioral observation data entry apps |
GazeCapture | From scientific research to commercial applications, eye tracking is an important tool across many domains. Despite its range of applications, eye tracking has yet to become a pervasive technology. We believe that we can put the power of eye tracking in everyone's palm by building eye tracking software that works on co... | Provide a detailed description of the following dataset: GazeCapture |
Gaze360 | Understanding where people are looking is an informative social cue. In this work, we present Gaze360, a large-scale gaze-tracking dataset and method for robust 3D gaze estimation in unconstrained images. Our dataset consists of 238 subjects in indoor and outdoor environments with labelled 3D gaze across a wide range o... | Provide a detailed description of the following dataset: Gaze360 |
Rare Diseases Mentions in MIMIC-III | ## Data annotation
The 1,073 full rare disease mention annotations (from 312 MIMIC-III **discharge summaries**) are in [`full_set_RD_ann_MIMIC_III_disch.csv`](https://github.com/acadTags/Rare-disease-identification/blob/main/data%20annotation/full_set_RD_ann_MIMIC_III_disch.csv).
The data split:
* the first 400 ... | Provide a detailed description of the following dataset: Rare Diseases Mentions in MIMIC-III |
APPS | The APPS dataset consists of problems collected from different open-access coding websites such as Codeforces, Kattis, and more. The APPS benchmark attempts to mirror how humans programmers are evaluated by posing coding problems in unrestricted natural language and evaluating the correctness of solutions. The problems... | Provide a detailed description of the following dataset: APPS |
BigCQ | **BigCQ** is a dataset of Competency Question templates paired with SPARQL-OWL query templates. These represent templates of ontology requirements formalizations which are then translated into SPARQL-OWL query language used to query T-Box level of ontologies. Thus, such a dataset can be used in various scenarios regard... | Provide a detailed description of the following dataset: BigCQ |
KLUE | Korean Language Understanding Evaluation (**KLUE**) benchmark is a series of datasets to evaluate natural language understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible to anyone without any restrictions. With ethical considerations in mind, we del... | Provide a detailed description of the following dataset: KLUE |
GBSG2 | The German Breast Cancer Study Group (GBSG2) dataset studies the effects of hormone treatment on recurrence-free survival time.
The event of interest is the recurrence of cancer time.
This data frame contains the observations of 686 women:
* horTh: hormonal therapy, a factor at two levels (yes and no).
* age: a... | Provide a detailed description of the following dataset: GBSG2 |
PBC | Primary sclerosing cholangitis is an autoimmune disease leading to destruction of the small bile ducts in the liver. Progression is slow but inexhortable, eventually leading to cirrhosis and liver decompensation. The condition has been recognised since at least 1851 and was named "primary biliary cirrhosis" in 1949. Be... | Provide a detailed description of the following dataset: PBC |
Toyota Smarthome dataset | Toyota Smarthome Trimmed has been designed for the activity classification task of 31 activities. The videos were clipped per activity, resulting in a total of 16,115 short RGB+D video samples. activities were performed in a natural manner. As a result, the dataset poses a unique combination of challenges: high intra-... | Provide a detailed description of the following dataset: Toyota Smarthome dataset |
VPCD | **VPCD** contains multi-modal annotations (face, body and voice) for all primary and secondary characters from a range of diverse TV-shows and movies. It is used for evaluating multi-modal person-clustering. It contains body-tracks for each annotated character, face-tracks when visible, and voice-tracks when speaking, ... | Provide a detailed description of the following dataset: VPCD |
MNIST Large Scale dataset | The **MNIST Large Scale dataset** is based on the classic [MNIST dataset](/dataset/mnist), but contains large scale variations up to a factor of 16. The motivation behind creating this dataset was to enable testing the ability of different algorithms to learn in the presence of large scale variability and specifically ... | Provide a detailed description of the following dataset: MNIST Large Scale dataset |
NewsTSC | **NewsTSC** is a dataset for target-dependent sentiment classification (TSC), to investigate TSC in news articles, a much less researched domain, despite the importance of news as an essential information source in individual and societal decision making. | Provide a detailed description of the following dataset: NewsTSC |
DeepCAD | **DeepCAD** is a CAD dataset consisting of 179,133 models and their CAD construction sequences. It can be used to train generative models of 3D shapes. | Provide a detailed description of the following dataset: DeepCAD |
UIT-ViWikiQA | The UIT-ViWikiQA is a dataset for evaluating sentence extraction-based machine reading comprehension in the Vietnamese language. The UIT-ViWikiQA dataset is converted from the UIT-ViQuAD dataset, consisting of 23,074 question-answers based on 5,109 passages of 174 Vietnamese articles from Wikipedia. | Provide a detailed description of the following dataset: UIT-ViWikiQA |
ZuBuD | The goal of the ZuBuD Image Database is to share image data sets with researcheres around the world. To facilitate this, we have created this site, which contains over 1005 images about Zurich city building. The detail information about the database can be found on our Technical Report:TR-260. | Provide a detailed description of the following dataset: ZuBuD |
A Billion Ways to Grasp | Robot grasping is often formulated as a learning problem. With the increasing speed and quality of physics simulations, generating large-scale grasping data sets that feed learning algorithms is becoming more and more popular. An often overlooked question is how to generate the grasps that make up these data sets. In t... | Provide a detailed description of the following dataset: A Billion Ways to Grasp |
The RBO Dataset of Articulated Objects and Interactions | The RBO dataset of articulated objects and interactions is a collection of 358 RGB-D video sequences (67:18 minutes) of humans manipulating 14 articulated objects under varying conditions (light, perspective, background, interaction). All sequences are annotated with ground truth of the poses of the rigid parts and the... | Provide a detailed description of the following dataset: The RBO Dataset of Articulated Objects and Interactions |
Clarkson Fingerprint Generator | Clarkson Fingerprint Generator consists of a dataset of 50K synthetically generated fingerprints. | Provide a detailed description of the following dataset: Clarkson Fingerprint Generator |
ReactionGIF | ReactionGIF is an affective dataset of 30K tweets which can be used for tasks like induced sentiment prediction and multilabel classification of induced emotions. | Provide a detailed description of the following dataset: ReactionGIF |
scb_name_length_data_Sweden_Stockholm_2019 | Appendix A in this paper contains a real-world name length data for the whole of Sweden as well as Stockholm Municipality (Swedish: Stockholms kommun) as of 31 December 2019. It excludes names that either belong to people with protected identities or are suspiciously incorrect due to errors in petition. But these excl... | Provide a detailed description of the following dataset: scb_name_length_data_Sweden_Stockholm_2019 |
DIBCO and H_DIBCO | The contest of binarization using a popular document database was organized called as Document Image Binarization Contest (DIBCO) from 2009 to 2019, except for 2015. | Provide a detailed description of the following dataset: DIBCO and H_DIBCO |
EPISURG | EPISURG is a clinical dataset of $T_1$-weighted magnetic resonance images (MRI) from 430 epileptic patients who underwent resective brain surgery at the National Hospital of Neurology and Neurosurgery (Queen Square, London, United Kingdom) between 1990 and 2018.
The NIfTI files are anonymised and the images have bee... | Provide a detailed description of the following dataset: EPISURG |
SICAPv2 | **SICAPv2** is a database containing prostate histology whole slide images with both annotations of global Gleason scores and path-level Gleason grades.
Data associated with the paper:
Silva-Rodríguez, J., Colomer, A., Sales, M. A., Molina, R., & Naranjo, V. (2020). Going deeper through the Gleason scoring scale... | Provide a detailed description of the following dataset: SICAPv2 |
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