cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57702/jmadpbkj
title: Building Data Genome 2.0 (BDG2)

description: Building energy prediction and management has become increasingly important in recent decades, driven by the growth of Internet of Things (IoT) devices and the availability of more energy data. However, energy data is often collected from multiple sources and can be incomplete or inconsistent, which can hinder accurate predictions and management of energy systems and limit the usefulness of the data for decision-making and research.
DOI: 10.57702/n07rs5bs
title: RealBasicVSR

description: RealBasicVSR dataset is used for upscaling the generated videos.
DOI: 10.57702/7a3itqsa
title: Pandemic Dataset

description: The dataset used in this paper for playing Pandemic, a cooperative board game.
DOI: 10.57702/pe0uf36v
title: PaccMannRL: Designing anticancer drugs from transcriptomic data via reinforcement learning

description: The dataset used in the paper is a collection of gene expression profiles from cancer cells, as well as a collection of bioactive small molecules.
DOI: 10.57702/zvwpwo4k
title: CIFAR10/100, ImageNet, and CUB-200

description: The dataset used in this paper is CIFAR10/100, ImageNet, and CUB-200.
DOI: 10.57702/3kn33ual
title: Wikipedia Comparable Corpora

description: Multilingual dataset for topic modeling based on aligned Wikipedia articles extracted from Wikipedia Comparable Corpora
DOI: 10.57702/v84dbv9p
title: CORD-19 Research Challenge

description: COVID-19 research challenge dataset
DOI: 10.57967/hf/3701
title: marchev-synth-data
DOI: 10.57702/8bqsckpp
title: Bridges Dataset

description: A dataset for bridge detection and identification in VHR RSIs, containing 500 images with 4,800 × 2,843 pixels.
DOI: 10.57702/xr2qfd2k
title: DOTA-v1.0

description: A large-scale dataset for object detection in aerial images, containing 2,541 bridges in 288 images.
DOI: 10.57702/b9m0p7em
title: Wind Turbine Blade Anomaly Detection Dataset

description: The dataset used in this paper for anomaly detection in wind turbine blades using FMCW radar.
DOI: 10.57702/2xc8yfrz
title: BOBBY2: Buffer Based Robust High-Speed Object Tracking

description: A novel high-speed single object tracker that is robust against non-semantic distractor exemplars is introduced; dubbed BOBBY2.
DOI: 10.57702/viaihrk7
title: TU-3 UAV dataset

description: A small yet challenging custom UAV dataset.
DOI: 10.15468/dl.3376jh
title: Occurrence Download

description: A dataset containing 145421 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phaethornis striigularis Gould, 1854"
 ]
}

 The dataset includes 145421 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013414-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/7u9ark2u
title: SIDD+

description: The dataset used for training and testing the proposed method for image denoising.
DOI: 10.57702/zavf8owl
title: OAMatcher: An Overlapping Areas-based Network for Accurate Local Feature Matching

description: Local feature matching is an essential component in many visual applications. In this work, we propose OAMatcher, a detector-free method that imitates humans behavior to realize accurate and dense local feature matching.
DOI: 10.57702/yv5yc1z0
title: Scannet

description: The dataset used for training and testing the proposed RGBD-based obstacle avoidance system for visually impaired people.
DOI: 10.57702/px86c7d9
title: RobustSwap: A Simple yet Robust Face Swapping Model

description: Face swapping aims at injecting a source image’s identity (i.e., facial features) into a target image, while strictly preserving the target’s attributes, which are irrelevant to identity.
DOI: 10.57702/u6mnblor
title: Deep Face Recognition

description: The VGGFace dataset is a large-scale face recognition dataset containing over 2.6 million images of 9,131 subjects.
DOI: 10.57702/0246q780
title: CelebV-HQ: A Large-Scale Video Facial Attributes Dataset

description: CelebV-HQ: A large-scale video facial attributes dataset.
DOI: 10.57702/ssggrjhh
title: X-HRNet: Towards Lightweight Human Pose Estimation with Spatially Unidimensional Self-Attention

description: High-resolution representation is necessary for human pose estimation to achieve high performance, and the ensuing problem is high computational complexity.
DOI: 10.57702/0z2a5znk
title: Sentiment Polarity (SP) Dataset

description: The dataset contains agent classiﬁcations for movie comments. All the movie comments are from the website Rotten Tomatoes. Agents were asked to annotate each comment as either positive (1) or negative (0).
DOI: 10.57702/oo2hl76z
title: Weather Sentiment (CF) Dataset

description: The dataset contains movie evaluations from IMDB and social network information from Twitter. The ratings on the IMDB website are based on the aggregated evaluations from all users, and the observations come from only a subset of users who share their ratings on Twitter.
DOI: 10.57702/mzeagdo0
title: A DenseNet Based Approach for Multi-Frame In-Loop Filter in HEVC

description: The proposed MIF approach enhances the quality of each encoded frame leveraging multiple adjacent frames.
DOI: 10.57702/4k0atj6d
title: Reaction-diﬀusion model

description: The dataset used in this paper is a reaction-diﬀusion model, which is a mathematical model that describes the behavior of particles in a reaction-diﬀusion system.
DOI: 10.57702/nwknm7f4
title: OpenAssistant

description: The authors used the OpenAssistant dataset to construct evaluation datasets for their attacks.
DOI: 10.57702/v0xrgy5d
title: Penn action dataset

description: The Penn action dataset is a collection of videos of human actions performed by different people with different variations.
DOI: 10.15468/dl.gyzwtb
title: Occurrence Download

description: A dataset containing 292 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astrophytum asterias (Zucc.) Lem."
 ]
}

 The dataset includes 292 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013512-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ng6k64
title: Occurrence Download

description: A dataset containing 103 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Mamíferos de la Ecoreserva Predio Refinería (Barrancabermeja, Santander) - Proyecto FIBRAS"
 ]
}

 The dataset includes 103 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013508-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wss92b
title: Occurrence Download

description: A dataset containing 11315 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Panthera onca (Linnaeus, 1758), Vicugna vicugna (Molina, 1782))"
 ]
}

 The dataset includes 11315 records from 282 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013513-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k5vvcc
title: Occurrence Download

description: A dataset containing 625 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Angelonia angustifolia Benth."
 ]
}

 The dataset includes 625 records from 88 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013511-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8q5f25
title: Occurrence Download

description: A dataset containing 140 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is one of (North America, South America)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pepsis grossa Smith, 1855",
 "Year 1846-2024"
 ]
}

 The dataset includes 140 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013515-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u4qrc9
title: Occurrence Download

description: A dataset containing 103 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Mamíferos de la Ecoreserva Predio Refinería (Barrancabermeja, Santander) - Proyecto FIBRAS"
 ]
}

 The dataset includes 103 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013510-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8n4ywa
title: Occurrence Download

description: A dataset containing 2452 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vicugna vicugna (Molina, 1782)"
 ]
}

 The dataset includes 2452 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013507-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/k53quweg
title: RangeDet: In Defense of Range View for LiDAR-Based 3D Object Detection

description: A LiDAR-based 3D object detection dataset.
DOI: 10.57702/c9aelxa5
title: Reference-tracking control experiments with a heavy-duty machine

description: The dataset used in the paper is a set of reference-tracking control experiments with a heavy-duty machine.
DOI: 10.57702/at9jge66
title: Music-AVQA

description: The Music-AVQA dataset contains multiple question-and-answer pairs, with 9,288 videos and 45,867 question-and-answer pairs.
DOI: 10.57702/17jatdtu
title: AVQA

description: The AVQA dataset contains 57,015 videos and 57,335 question-and-answer pairs.
DOI: 10.21227/xgad-sa62
title: Asian subcontinent dataset (ASCD)

description: The Asian Subcontinent Dataset (ASCD) is a multisensor dataset that includes geospatial data collected from different countries within the Asian subcontinent, specifically India, Bangladesh, and Sri Lanka. The dataset consists of imagery captured through two main sources: Google Earth Pro software and IKONOS-2 satellite images. ASCD includes 14 distinct land cover classes, ranging from urban areas to natural environments, with 1,674 images. The number of images in each land cover class varies between 100 and 204. Each image in the dataset has a resolution of 227 × 227 pixels and includes three color channels. This dataset provides a valuable resource for research in remote sensing, land cover classification, and environmental monitoring in the Asian subcontinent.
DOI: 10.5281/zenodo.13982588
title: Nanoengineered Shape-memory Hemostat - Dataset

description: This data set contains all raw data and data analysis files associated with the following manuscript: 

Nanoengineered Shape‐Memory Hemostat

Article DOI: 10.1002/smsc.202400321

Published in Small Science by Wiley-VCH GmbH.

 

Authors: Sarah E. Hargett# (1), Giriraj K. Lokhande# (1), Joseph Duran (1), Zanir Hirani (1), Lindy K. Jang (1,2), Samantha Foster (3), Kaivalya A. Deo (1), Sasha George (4), Mahjabeen Javed (1), Taylor H. Ware (1,4), Duncan J. Maitland* (1), Akhilesh K. Gaharwar* (1,3,4,5)

#Equally contributed

*Corresponding authors

 

1. Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA

2. Materials Engineering Division, Lawrence Livermore National Laboratory, Livermore, CA, 94550, USA

3. Interdisciplinary Program in Genetics, Texas A&M University, College Station, TX, 77843, USA

4. Department of Materials Science and Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA

5. Center for Remote Health Technologies and Systems, Texas A&M University, College Station, TX, 77843, USA

 

Funding information: 

Department of Defense: W81XWH2210932

American Heart Association: 24PRE1200460

Division of Materials Research: 2041671

National Institute of Biomedical Imaging and Bioengineering: EB026265

Texas A&M University
DOI: 10.5281/zenodo.13982589
title: Nanoengineered Shape-memory Hemostat - Dataset

description: This data set contains all raw data and data analysis files associated with the following manuscript: 

Nanoengineered Shape‐Memory Hemostat

Article DOI: 10.1002/smsc.202400321

Published in Small Science by Wiley-VCH GmbH.

 

Authors: Sarah E. Hargett# (1), Giriraj K. Lokhande# (1), Joseph Duran (1), Zanir Hirani (1), Lindy K. Jang (1,2), Samantha Foster (3), Kaivalya A. Deo (1), Sasha George (4), Mahjabeen Javed (1), Taylor H. Ware (1,4), Duncan J. Maitland* (1), Akhilesh K. Gaharwar* (1,3,4,5)

#Equally contributed

*Corresponding authors

 

1. Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA

2. Materials Engineering Division, Lawrence Livermore National Laboratory, Livermore, CA, 94550, USA

3. Interdisciplinary Program in Genetics, Texas A&M University, College Station, TX, 77843, USA

4. Department of Materials Science and Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA

5. Center for Remote Health Technologies and Systems, Texas A&M University, College Station, TX, 77843, USA

 

Funding information: 

Department of Defense: W81XWH2210932

American Heart Association: 24PRE1200460

Division of Materials Research: 2041671

National Institute of Biomedical Imaging and Bioengineering: EB026265

Texas A&M University
DOI: 10.57702/cpd1jln8
title: CLAMNET: Using Contrastive Learning with Variable Depth Unets for Medical Image Segmentation

description: The dataset used in this paper is medical images from various sources including magnetic resonance imaging (MRI) and computed tomography (CT), without the need for pixel-wise annotations.
DOI: 10.57702/3hf4wlku
title: STACOM MICCAI 2018 challenge

description: A 3D CNN for automatic segmentation of the left atrial chamber in 3D gadolinium enhanced-MRI volumes of patients diagnosed with atrial fibrillation.
DOI: 10.57702/dd9xqp99
title: PASCAL-5i and COCO-20i

description: PASCAL-5i and COCO-20i are datasets used for evaluation of few-shot segmentation.
DOI: 10.57702/5hahv5rs
title: LV-BERT: Exploiting Layer Variety for BERT

description: Modern pre-trained language models are mostly built upon backbones stacking self-attention and feed-forward layers in an interleaved order. This paper aims to improve pre-trained models by exploiting layer variety from two aspects: the layer type set and the layer order.
DOI: 10.57702/esa9025o
title: Stanford Question Answering Dataset (SQuAD 1.1)

description: The Stanford Question Answering Dataset (SQuAD 1.1) is a dataset of more than 100K questions which all can be answered by locating a span of text from the corresponding context passage.
DOI: 10.57702/29ycgxdq
title: Stanford Question Answering Dataset (SQuAD 2.0)

description: The Stanford Question Answering Dataset (SQuAD 2.0) supplements the SQuAD 1.1 with over 50K unanswerable questions.
DOI: 10.17909/pydq-xz94
title: Data from A Spectroscopically Calibrated Prescription for Extracting PAH Flux from JWST MIRI Imaging

description: JWST MIRI/IFU spectroscopy of LIRGs in GOALS ERS sample
DOI: 10.57702/vn86r7c5
title: Gabor Layers Enhance Network Robustness

description: The dataset used in this paper is MNIST, SVHN, CIFAR10, CIFAR100, and ImageNet.
DOI: 10.57702/t2p96pch
title: PSDNet: Determination of Particle Size Distributions Using Synthetic Soil Images

description: The dataset used for training and testing the ConvNet model for PSD determination.
DOI: 10.57702/dqlgjjzq
title: GRAINet: Mapping Grain Size Distributions in River Beds from UAV Images

description: The dataset used for training and testing the GRAINet model for PSD determination.
DOI: 10.57702/8rj9jhfc
title: Technical Feasibility of Creating a Beach Grain Size Database with Citizen Scientists

description: The dataset used for training and testing the SediNet model for PSD determination.
DOI: 10.57702/merp4303
title: DTU Multi-View Stereo

description: The dataset contains 80 real-world scenes with image sequences and structured light 3D scans as reference data.
DOI: 10.57702/quwmen0m
title: DeepVoxels-Real Dataset

description: The dataset contains five tabletop real scenes imaged by 352 cameras in a dome.
DOI: 10.57702/yn8awoee
title: DreamFusion gallery

description: The dataset used in the TextMesh paper, containing 35 text prompts for 3D mesh generation.
DOI: 10.57702/req6hl1j
title: A three-year dataset supporting research on building energy management and occupancy analytics

description: The dataset is a three-year dataset supporting research on building energy management and occupancy analytics.
DOI: 10.57702/ufk48l6q
title: AAPM 256×256

description: The dataset used in this paper for 3D CT reconstruction.
DOI: 10.15468/dl.zgzx2v
title: Occurrence Download

description: A dataset containing 138822 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Luzula sylvatica (Huds.) Gaudin)"
 ]
}

 The dataset includes 138822 records from 852 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013410-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30296635
title: VR29 baseline PBMC TCR repertoire - unstimulated

description: Baseline TCR beta CDR3 sequencing from unstimulated CD8-depleted PBMCs
DOI: 10.6084/m9.figshare.30296635.v1
title: VR29 baseline PBMC TCR repertoire - unstimulated

description: Baseline TCR beta CDR3 sequencing from unstimulated CD8-depleted PBMCs
DOI: 10.13145/bacdive4001.20251217.10
title: Desulfosalsimonas propionicica Kjeldsen et al. 2010

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0072241.10fu
title: SH0072241.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive4002.20250331.9.3
title: Desulfobulbus elongatus Samain et al. 1985

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive4002.20251217.10
title: Desulfobulbus elongatus Samain et al. 1985

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0072242.10fu
title: SH0072242.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive4003.20241212.9.2
title: Desulfobulbus elongatus Samain et al. 1985

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive4003.20251217.10
title: Desulfobulbus elongatus Samain et al. 1985

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive4004.20250331.9.3
title: Desulfobulbus propionicus Widdel 1981

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive4004.20251217.10
title: Desulfobulbus propionicus Widdel 1981

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0072243.10fu
title: SH0072243.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive4005.20241212.9.2
title: Desulfobulbus propionicus Widdel 1981

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.