cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57702/gcyd7yh2
title: KIT Motion Language dataset

description: The KIT Motion Language dataset provides 3911 motion sequences and 6353 sequence-level natural language descriptions.
DOI: 10.57702/hrcewbd2
title: ERA5 Reanalysis Dataset

description: The dataset used in this paper is the ERA5 reanalysis dataset, which contains climate parameters such as Mean sea level pressure, Surface pressure, Sea surface temperature, 100 metre U wind component, 100 metre V wind component, 10 metre U wind component, 10 metre V wind component, 2 metre dewpoint temperature, 2 metre temperature.
DOI: 10.57702/p1r6advt
title: Weather2K Dataset

description: The Weather2K dataset is used for downscaling, which includes hourly observations of 20 meteorological variables from 1866 ground observation stations.
DOI: 10.57702/6hsrnarm
title: PhysioNet Challenge 2021

description: The dataset used in this paper is a collection of electrocardiogram (ECG) signals from healthy individuals, with a focus on accurately capturing the subtleties of ECG morphology.
DOI: 10.57702/b1b5qapw
title: ESBD

description: Expanded Stereotype Behavior Dataset (ESBD)
DOI: 10.57702/k3wlsa1z
title: SSBD

description: Self-Stimulatory Behavior Dataset (SSBD)
DOI: 10.57702/ffzf63sc
title: Digital Image Based Identification of Rice Variety

description: Digital image based identification of rice variety using image processing and neural network.
DOI: 10.57702/mmvmwrhs
title: Distilling Object Detectors with Global Knowledge

description: Knowledge distillation learns a lightweight student model that mimics a cumbersome teacher. Existing methods regard the knowledge as the feature of each instance or their relations, which is the instance-level knowledge only from the teacher model, i.e., the local knowledge. However, the empirical studies show that the local knowledge is much noisy in object detection tasks, especially on the blurred, occluded, or small instances.
DOI: 10.57702/domiz1zb
title: Make-a-protagonist: Generic video editing with an ensemble of experts

description: Make-a-protagonist: Generic video editing with an ensemble of experts.
DOI: 10.57702/outq835j
title: MotionGS

description: A 3DGS-based SLAM approach that integrates deep visual features, dual keyframe selection, and 3DGS.
DOI: 10.57702/ep7718s7
title: TUM RGB-D Dataset

description: A benchmark for the evaluation of RGB-D SLAM systems.
DOI: 10.57702/ec8y4ce5
title: Atherosclerotic Carotid Plaque Detection using Deep Learning

description: A small dataset of 65 panoramic images for automatic detection of atherosclerotic carotid plaques.
DOI: 10.15468/dl.6g6vze
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((121 42,128 42,128 49,121 49,121 42))",
 "TaxonKey is Aix galericulata (Linnaeus, 1758)",
 "Year 2000-2024"
 ]
}

 The dataset includes 50 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014113-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/o1c065x3
title: Neural Distributed Source Coding

description: Distributed source coding (DSC) is the task of encoding an input in the absence of correlated side information that is only available to the decoder.
DOI: 10.15468/dl.qh7mke
title: Occurrence Download

description: A dataset containing 788 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dasyatis centroura (Mitchill, 1815)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 788 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014116-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/6bxp7uw0
title: KITTI Stereo 2012 and 2015

description: KITTI Stereo 2012 and 2015 dataset.
DOI: 10.57702/bzf3euwi
title: Integrated Interaction Database (IID) networks

description: The dataset used in this paper is the Integrated Interaction Database (IID) networks, which contain protein-protein interaction (PPI) networks for various species.
DOI: 10.15468/dl.j8czgp
title: Occurrence Download

description: A dataset containing 14206 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Coris julis (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 14206 records from 83 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014115-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yq2tan
title: Occurrence Download

description: A dataset containing 8816 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Conger conger (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8816 records from 183 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014114-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/8fftme13
title: ZJU-MoCap Dataset

description: The ZJU-MoCap dataset is a prominent benchmark in human modeling from videos. The dataset includes 6 human subjects, each with 100 frames collected from one camera for training and the remaining cameras for evaluation.
DOI: 10.57702/a5lulfow
title: BFRnet: A deep learning-based MR background field removal method for QSM

description: A deep learning-based method for background field removal in MRI, specifically for QSM in the brain containing significant pathological susceptibility sources
DOI: 10.57702/byvtfn4w
title: COVID-19 Severity Classification on Chest X-ray Images

description: Chest X-ray images dataset used for COVID-19 severity classification
DOI: 10.57702/2snr63fd
title: normal-chest-xray-pa-dataset

description: Chest X-ray images dataset for COVID-19 pneumonia detection
DOI: 10.57702/t6vblzw0
title: LAION-Styles

description: A dataset for style attribution, curating images associated with the artist that created them.
DOI: 10.57702/p1tohz4m
title: Electric Powertrain Dataset

description: The dataset used in this paper is a convex model of the EV powertrain, including the loss models of the EM, the thermal models, and the performance requirements.
DOI: 10.5281/zenodo.14251254
title: Glass Frog Calls

description: This dataset contains 5296 audio files in .WAV format, corresponding to calls of two glass frog species: Hyalinobatrachium fleischmanni (Hf) and Espadarana prosoblepon (Ep), recorded under controlled laboratory conditions. We further increased the dataset size using noise injection-based data augmentation in one species (Ep), and artificially shifting call frequency in both species. The dataset contains four labelled classes: Hf (1250 calls), Hf-shifted (1250 calls), Ep (1398 calls) and Ep-shifted (1398 calls); each class is in a separate folder.

Noise injected files, with white and pink noise, were generated using noise factors of 0.010 and 0.020, respectively, using the random and powerlaw_psd_gaussian functions from numpy (v1.26.4) and colorednoise (v2.2.0) Python libraries.

Frequency shifting placed calls in upper or lower parts of spectrum, incorporating additional variability and was used to create two new classes. Hf call frequency was increased by a factor of +4 semitones (4/12), while Ep call frequency was decreased by the same factor (-4), using librosa (v0.10.2) in Python (effects.pitch_shift). Modified calls (‘Hf-shifted’ and ‘Ep-shifted’, respectively) more closely resemble the calls of the other species in terms of their frequency band.

Derived audio files partially share file names: '1104-18211-ROI1_pN.WAV' is the 'pink noise' version of '1104-18211-ROI1.WAV', etc.

The audio collection is accompanied by a data table (.csv) with no missing or null values, and consists of 4 columns: “File_name”; “Data_Augmentation”, whether the file had noise injection or not, and its type (white or pink); “Frequency_Shift”, whether the audio frequency was artificially shifted or not; and “Class”, which includes the respective labels. The dataset is suitable for machine learning tasks, audio signal processing and statistical analysis.
DOI: 10.5281/zenodo.14251255
title: Glass Frog Calls

description: This dataset contains 5296 audio files in .WAV format, corresponding to calls of two glass frog species: Hyalinobatrachium fleischmanni (Hf) and Espadarana prosoblepon (Ep), recorded under controlled laboratory conditions. We further increased the dataset size using noise injection-based data augmentation in one species (Ep), and artificially shifting call frequency in both species. The dataset contains four labelled classes: Hf (1250 calls), Hf-shifted (1250 calls), Ep (1398 calls) and Ep-shifted (1398 calls); each class is in a separate folder.

Noise injected files, with white and pink noise, were generated using noise factors of 0.010 and 0.020, respectively, using the random and powerlaw_psd_gaussian functions from numpy (v1.26.4) and colorednoise (v2.2.0) Python libraries.

Frequency shifting placed calls in upper or lower parts of spectrum, incorporating additional variability and was used to create two new classes. Hf call frequency was increased by a factor of +4 semitones (4/12), while Ep call frequency was decreased by the same factor (-4), using librosa (v0.10.2) in Python (effects.pitch_shift). Modified calls (‘Hf-shifted’ and ‘Ep-shifted’, respectively) more closely resemble the calls of the other species in terms of their frequency band.

Derived audio files partially share file names: '1104-18211-ROI1_pN.WAV' is the 'pink noise' version of '1104-18211-ROI1.WAV', etc.

The audio collection is accompanied by a data table (.csv) with no missing or null values, and consists of 4 columns: “File_name”; “Data_Augmentation”, whether the file had noise injection or not, and its type (white or pink); “Frequency_Shift”, whether the audio frequency was artificially shifted or not; and “Class”, which includes the respective labels. The dataset is suitable for machine learning tasks, audio signal processing and statistical analysis.
DOI: 10.57702/5x4rybjy
title: DISCO

description: The dataset used for crowd counting.
DOI: 10.57702/zgmzvwmd
title: Variational Dynamics Encoder (VDE) dataset

description: The dataset used in the paper is a collection of time-series data for protein dynamics, specifically the 2-D M¨uller-Brown potential and the villin headpiece domain.
DOI: 10.57702/mxglevg0
title: International Skin Imaging Collaboration (ISIC) 2019

description: The International Skin Imaging Collaboration (ISIC) 2019 dataset is a multi-source dataset for dermoscopic lesion classification. It consists of 25,531 images corresponding to 13,931 different lesions from three sources: Vienna (HAM), Barcelona (BCN), and New York (MSK).
DOI: 10.57702/qe1x02tu
title: BCN20000

description: The BCN20000 dataset is a collection of dermoscopic images of skin lesions from Barcelona.
DOI: 10.15129/df94ccea-ee17-451c-a243-8d36fbb7c7e5
title: Replication files: Intergovernmental cooperation networks, national policy positions and partisan ideologies: Longitudinal evidence from the Council of the European Union

description: Accepted by Journal of European Public Policy
DOI: 10.15468/dl.aazkgb
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Rhus teniana Hand.-Mazz."
 ]
}

 The dataset includes 20 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014117-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/tb46c58v
title: QMUL-Chair-V2

description: Fine-grained sketch-based image retrieval (FG-SBIR) aims to minimize the distance between sketches and corresponding images in the embedding space.
DOI: 10.57702/g4dln2v6
title: Credibility evaluation of income data with hierarchical correlation reconstruction

description: Polish household budget survey data used for credibility evaluation of income data
DOI: 10.57702/vu5zk1fq
title: COVID CT-Net: Predicting Covid-19 From Chest CT Images Using Attentional Convolutional Network

description: COVID-19 CT dataset for predicting COVID-19 from chest CT images using attentional convolutional network.
DOI: 10.57702/sp1j5ug1
title: Black-box Targeted Adversarial Attack on Segment Anything (SAM)

description: This work conducts the first yet comprehensive study on TAA on SAM in a black-box setup, assuming no access to prompt and model.
DOI: 10.57702/y5cmonzv
title: Segment Anything Model (SAM)

description: SAM is a foundation model in computer vision that can segment anything.
DOI: 10.57702/lossuboh
title: Robustness of SAM: Segment Anything under corruptions and beyond

description: This work investigates the robustness of SAM to corruptions and adversarial attacks.
DOI: 10.57702/kzz2csje
title: SalsaNext

description: SalsaNext dataset for 3D LiDAR point cloud semantic segmentation
DOI: 10.57702/qlatti2b
title: Celeba

description: The dataset used in this paper is a collection of images, and the authors used it to train and evaluate Variational Autoencoders (VAEs).
DOI: 10.57702/ru1tbev9
title: ETH-UCY

description: A collection of relatively small benchmark pedestrian crowd datasets.
DOI: 10.57702/kx7ymshw
title: eICU and MIMIC-IV

description: The eICU and MIMIC-IV datasets are used for out-of-distribution detection in medical tabular data.
DOI: 10.57702/nvpckfzc
title: HIV and FIV protease peptides

description: Dataset of native and non-native peptides for HIV and FIV proteases
DOI: 10.5281/zenodo.14264790
title: Non-Medical Action Policy An Integrated Effort to Improve Health Services
DOI: 10.5281/zenodo.14264791
title: Non-Medical Action Policy An Integrated Effort to Improve Health Services
DOI: 10.57702/w3g3wdvz
title: Face Mask Detection and Classification Dataset

description: The dataset is used for face mask detection and classification. It contains images of people wearing masks, not wearing masks, and wearing masks incorrectly.
DOI: 10.57702/x4hbi43f
title: A New Action Recognition Framework for Video Highlights

description: A sports video highlight summarization framework using YOLO v3 and OpenPose.
DOI: 10.57702/2nxs563g
title: Set 5

description: Validation set for image restoration
DOI: 10.57702/hhtte0mp
title: Light Field Dataset

description: The dataset used in the paper is a light field dataset, which is a 4D representation of light field data. The dataset is used to test the proposed method for deblurring light fields.
DOI: 10.57702/urhgy3i2
title: Inter- and Intra-Series Embeddings Fusion Network for Epidemiological Forecasting

description: The proposed model SEFNet is used for epidemic forecasting. It extracts inter- and intra-series embeddings from two parallel modules and fuses them using parametric-matrix fusion for prediction.
DOI: 10.57702/vk7vlxs4
title: Japan-Prefectures

description: The dataset contains weekly influenza-like-illness statistics from 47 prefectures in Japan, ranging from August 2012 to March 2019.
DOI: 10.57702/wtnpdeow
title: US-Regions

description: The dataset contains weekly influenza activity levels for 10 HHS regions of the U.S. mainland for the period of 2002 to 2017.
DOI: 10.15468/dl.jdetmh
title: Occurrence Download

description: A dataset containing 3124 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Quercus myrsinifolia Blume"
 ]
}

 The dataset includes 3124 records from 122 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014118-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/xx7nz3di
title: M3IT

description: The M3IT dataset is a multimodal instruction tuning dataset, consisting of 80,000 images and their corresponding instructions.
DOI: 10.57702/qz5utx1k
title: CLIP-PAE

description: CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable and Controllable Text-Guided Face Manipulation
DOI: 10.57702/51nilqud
title: Procgen Dataset

description: The dataset used in the experiments, which contains procedurally generated environments.
DOI: 10.15468/dl.24m9kr
title: Occurrence Download

description: A dataset containing 7386 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Quercus michauxii Nutt."
 ]
}

 The dataset includes 7386 records from 203 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014119-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/r14fobl4
title: TxtDiffusionForensics

description: The TxtDiffusionForensics dataset, which consists of a diffusion model and the corresponding text pairs.
DOI: 10.57702/kio3febj
title: Autism Diagnostic Observation Schedule (ADOS) and Kaggle Facial Feature Image Dataset

description: The dataset used for the social behavior based module is the Autism Diagnostic Observation Schedule (ADOS) database, which provides social behavior data. The dataset used for the facial feature based module is the Kaggle database, which provides facial feature image data. The dataset used for the hybrid model is the Numerical Social Behavior database (NSB) and the Videos and Image Facial Feature database (VIFF).
DOI: 10.57702/ziw1wj9i
title: WSSS4LUAD Challenge Dataset

description: The WSSS4LUAD challenge dataset contains 10,091 patch-level annotations and over 130 million labeled pixels from 87 WSIs of lung adenocarcinoma.
DOI: 10.57702/urg123bj
title: SPED

description: Specific Places Dataset (SPED) used for testing the proposed BNN for VPR.
DOI: 10.57702/xf8rxz9m
title: Old City

description: Old City dataset used for testing the proposed BNN for VPR.
DOI: 10.57702/6qjmwz3c
title: Combined

description: Combined dataset used for testing the proposed BNN for VPR.
DOI: 10.57702/9uwnrsl6
title: The multimodal brain tumor image segmentation benchmark (brats)

description: The multimodal brain tumor image segmentation benchmark (brats).
DOI: 10.57702/p4wsgwux
title: SOCOFing dataset

description: The SOCOFing dataset is used for fingerprint identification and enhancement. It contains 6,000 fingerprints taken from 600 Africans.
DOI: 10.57702/0c348zwy
title: Faces, Genes, FTSE 100 datasets

description: Faces dataset, Genes dataset, FTSE 100 dataset
DOI: 10.57702/3wz9gc4q
title: TVSum

description: Automatic keyframe detection from videos is an exercise in selecting scenes that can best summarize the content for long videos.
DOI: 10.57702/uap93zif
title: GeoMultiTaskNet: remote sensing unsupervised domain adaptation using geographical coordinates

description: Land cover maps are a pivotal element in a wide range of Earth Observation (EO) applications. However, annotating large datasets to develop supervised systems for remote sensing (RS) semantic segmentation is costly and time-consuming. Unsupervised Domain Adaptation (UDA) could tackle these issues by adapting a model trained on a source domain, where labels are available, to a target domain, without annotations.
DOI: 10.57702/onvi44ko
title: Global Table Extractor (GTE)

description: Global Table Extractor (GTE): A Framework for Joint Table Identiﬁcation and Cell Structure Recognition Using Visual Context
DOI: 10.57702/5s9tgshg
title: ICDAR 2019 competition on table detection and recognition (CTDR)

description: ICDAR 2019 competition on table detection and recognition (CTDR)
DOI: 10.57702/jtytsuq9
title: Cascadetabnet

description: Cascadetabnet: An approach for end to end table detection and structure recognition from image-based documents
DOI: 10.57702/12wbkyzm
title: Image-based table recognition: data, model, and evaluation

description: Image-based table recognition: data, model, and evaluation.
DOI: 10.57702/ttn4s8ar
title: MIXSPEECH: DATA AUGMENTATION FOR LOW-RESOURCE AUTOMATIC SPEECH RECOGNITION

description: MixSpeech is a data augmentation method for automatic speech recognition, which trains an ASR model by taking a weighted combination of two different speech features as the input, and recognizing both text sequences.
DOI: 10.57702/mtdz50sv
title: SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

description: SpecAugment is a data augmentation method for automatic speech recognition, which masks the mel-spectrogram along the time and frequency axes.
DOI: 10.57702/2xominpl
title: The Wall Street Journal Corpus

description: The WSJ dataset is a large dataset of speech recordings, each containing a single speaker speaking a sentence.
DOI: 10.57702/4xdxh3es
title: HKUST/MTS: A Very Large Scale Mandarin Telephone Speech Corpus

description: The HKUST dataset is a large dataset of speech recordings, each containing a single speaker speaking a sentence.
DOI: 10.57702/xerte2mh
title: COCO 2017 Dataset

description: The COCO 2017 Dataset is a large-scale benchmark dataset for object detection, semantic segmentation, and instance segmentation.
DOI: 10.57702/14rxq3go
title: Dogs vs. Cats

description: The dataset used in the paper is Dogs vs. Cats, a binary classification dataset containing 3,000 dog and cat images.
DOI: 10.57702/vp7nrjo7
title: AffectNet: A Large-Scale Facial Expression Recognition Dataset

description: AffectNet is a large-scale facial expression recognition dataset that contains over one million facial images collected from the Internet.
DOI: 10.57702/cjz5z1fq
title: Affect-in-Wild: Valence and Arousal Prediction in the Wild

description: Affect-in-Wild is a dataset for valence and arousal prediction in the wild.
DOI: 10.57702/6fj214rh
title: FER2013: Facial Expression Recognition Dataset

description: FER2013 is a facial expression recognition dataset.
DOI: 10.57702/q0fe7mmh
title: Horse2Zebra, BBBC021, Organoids

description: Horse2Zebra dataset, BBBC021 dataset, Organoids dataset
DOI: 10.57702/3av53oer
title: ECOVNet: An Ensemble of Deep Convolutional Neural Networks for COVID-19 Detection from Chest X-Rays

description: The proposed architecture uses a CNN-based approach to detect COVID-19 from chest X-ray images. The dataset is used to train and evaluate the proposed model.
DOI: 10.15468/dl.mgvhvp
title: Occurrence Download

description: A dataset containing 690 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 (Stipa gigantea Link)"
 ]
}

 The dataset includes 690 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014121-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/brdq8met
title: Baikal-GVD

description: Baikal-GVD is a large-volume water-based neutrino telescope aimed at studying the flux of high-energy cosmic neutrinos and searching for their sources. The experiment is located in Lake Baikal, Russia, and, as of 2022, has an effective working volume of approximately 0.5 km3 with respect to the high-energy neutrino-induced cascades.
DOI: 10.57702/dn51gz9k
title: Monte-Carlo Simulations

description: Monte-Carlo simulations of Baikal-GVD's data. Two types of incoming particles are considered: 1) muon neutrinos arriving from under the horizon, and 2) bundles of muons originating from the cosmic air showers.