cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13301668
title: Sideways and Forward Soft Fracture: Additional Information and Data

description: This dataset contains the experimental raw data from the mechanical testing of soft elastomers with different mixing ratios to produce different crosslinking degrees. The data have not been filtered. 

Every specimen is tested under tensile loading until full rupture. All samples had a thickness of 2mm. The initial length between grips was set to 30mm. 

The files are named according to:

- the length of the pre-cut (c0mm/c1.2mm/c3.6mm/c6mm),

- the (average) strain rate (0.001s-1/0.1s-1),

- the mixing ratio (Xi0.5/Xi0.625/Xi0.75/Xi0.875/Xi1/Xi1.14/Xi1.33/Xi1.6/Xi2),

- the number of the experiment up to the total number of repetitions under the same test conditions (R1/R2/R3).

 

In addition, this dataset contains two videos showing the uniaxial deformation of:

a) a highly crosslinked sample (Xi = 1) that produces sideways fracturing,

b) a low-crosslinked sample (Xi = 0.5) that produces forward fracture.

 

If this dataset is used for research or industrial purposes, please cite:M.A. Moreno-Mateos, P. Steinmann. "Crosslinking degree variations enable programming and controlling soft fracture via sideways cracking", npj Computational Materials 10, 282 (2024). https://doi.org/10.1038/s41524-024-01489-y.Further explanation regarding the specimen preparation and experimental setup can be found in the aforementioned work.
DOI: 10.5281/zenodo.13301669
title: Sideways and Forward Soft Fracture: Additional Information and Data

description: This dataset contains the experimental raw data from the mechanical testing of soft elastomers with different mixing ratios to produce different crosslinking degrees. The data have not been filtered. 

Every specimen is tested under tensile loading until full rupture. All samples had a thickness of 2mm. The initial length between grips was set to 30mm. 

The files are named according to:

- the length of the pre-cut (c0mm/c1.2mm/c3.6mm/c6mm),

- the (average) strain rate (0.001s-1/0.1s-1),

- the mixing ratio (Xi0.5/Xi0.625/Xi0.75/Xi0.875/Xi1/Xi1.14/Xi1.33/Xi1.6/Xi2),

- the number of the experiment up to the total number of repetitions under the same test conditions (R1/R2/R3).

 

In addition, this dataset contains two videos showing the uniaxial deformation of:

a) a highly crosslinked sample (Xi = 1) that produces sideways fracturing,

b) a low-crosslinked sample (Xi = 0.5) that produces forward fracture.

 

If this dataset is used for research or industrial purposes, please cite:M.A. Moreno-Mateos, P. Steinmann. "Crosslinking degree variations enable programming and controlling soft fracture via sideways cracking", npj Computational Materials 10, 282 (2024). https://doi.org/10.1038/s41524-024-01489-y.Further explanation regarding the specimen preparation and experimental setup can be found in the aforementioned work.
DOI: 10.57702/bglnzdrz
title: Controlled Latent Space Sampling for Antimicrobial Peptide Design

description: A dataset of peptide sequences used for training and testing the proposed CLaSS method for controlled generation of antimicrobial peptides.
DOI: 10.57702/9nzbd4w1
title: Global Airborne Laser Scanning Data Providers Database (GlobALS)

description: Global Airborne Laser Scanning Data Providers Database (GlobALS)—A New Tool for Monitoring Ecosystems and Biodiversity.
DOI: 10.57702/ym9cuqms
title: GEDI

description: GEDI is a full-waveform LiDAR sensor onboard the International Space Station (ISS) that has been in operation between latitudes of 51.6° N and 51.6° S since 2019.
DOI: 10.15468/dl.8f9dn6
title: Occurrence Download

description: A dataset containing 178 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Exodeconus prostratus (Dombey ex L'Hér.) Raf."
 ]
}

 The dataset includes 178 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036975-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/lzclyvf5
title: MOTS Challenge

description: The MOTS Challenge dataset is a real-world video dataset consisting of pedestrian tracking and segmentation.
DOI: 10.57702/tds80xvn
title: ImageNet classiﬁcation

description: ImageNet classiﬁcation dataset, COCO dataset
DOI: 10.57702/761r79bp
title: Multilingual Blending: LLM Safety Alignment Evaluation with Language Mixture

description: Multilingual Blending: LLM Safety Alignment Evaluation with Language Mixture
DOI: 10.57702/dpoq4pv5
title: Fairchild dataset Indoor HDR Database

description: A large test set of 275 images gathered from the Fairchild dataset Indoor HDR Database.
DOI: 10.57702/hdz66qno
title: LVZ-HDR benchmark dataset

description: A dataset for tone mapping evaluation.
DOI: 10.57702/k2f6ohpn
title: ImageNet-Subset

description: ImageNet-Subset is a subset of the ImageNet dataset, containing 100 classes with 500 training images, 50 validation images, and 50 test images per class.
DOI: 10.57702/liahaagd
title: Decoy-MNIST

description: The dataset used in the paper is a synthetic dataset similar to decoy-MNIST of Ross et al. (2017) with induced shortcuts and is presented in Section 5.2. For evaluation on practical tasks, the authors evaluated on a plant phenotyping (Shao et al., 2021) task in Section 5.3, skin cancer detection (Rieger et al., 2020) task presented in Section 5.4, and object classification task presented in Section 5.5. All the datasets contain a known spurious feature, and were used in the past for evaluation of MLX methods.
DOI: 10.57702/bgw5cc5h
title: New York Times and 20Newsgroups datasets

description: The dataset used in the paper is the New York Times dataset and the 20Newsgroups dataset.
DOI: 10.57702/3pcpve95
title: Student’s t-Generative Adversarial Networks

description: Generative Adversarial Networks (GANs) have a great performance in image generation, but they need a large scale of data to train the entire framework, and often result in nonsensical results.
DOI: 10.57702/zbhf9bso
title: Forest management problem

description: The dataset used in this paper is a forest management problem, where the objective is to maintain an old forest for wildlife and make money by selling the cut wood.
DOI: 10.15468/dl.6sp8zb
title: Occurrence Download

description: A dataset containing 656 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-101.08636 23.2367,-101.15667 23.22571,-101.23005 23.19293,-101.23679 23.05041,-101.09844 22.95324,-100.91031 22.98719,-100.87896 23.09866,-100.93034 23.21622,-100.97737 23.23016,-101.00436 23.22929,-101.08636 23.2367))",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 656 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036976-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/00cmcq6p
title: Cartpole system

description: The dataset used in this paper is a Cartpole system, where the objective is to prevent the pole from falling over by pushing the cart to the left or to the right.
DOI: 10.57702/8x6sgize
title: Distilled Feature Fields Enable Open-Ended Manipulation

description: The dataset used in the paper is a collection of RGB images of a tabletop scene, along with their corresponding camera poses and 3D geometry.
DOI: 10.57702/seve0l1r
title: Improved Precision and Recall Metric for Assessing Generative Models

description: The dataset used in the paper is not explicitly described, but it is mentioned that it is a generative model dataset.
DOI: 10.57702/g491m0ya
title: AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit Detectors

description: Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic.
DOI: 10.57702/qjir9m02
title: BP4D: A Large-Scale Dataset for Facial Action Unit Detection

description: Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic.
DOI: 10.57702/i2fozm1q
title: DISFA: A Large-Scale Spontaneous Facial Action Intensity Database

description: Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic.
DOI: 10.57702/331vsbwl
title: CASME II: A Large-Scale Spontaneous Micro-Expression Database

description: Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic.
DOI: 10.57702/1o1zr7er
title: PolyphonicFormer: Uniﬁed Query Learning for Depth-aware Video Panoptic Segmentation

description: Depth-aware Video Panoptic Segmentation (DVPS) is a new challenging vision problem that aims to predict panoptic segmentation and depth in a video simultaneously.
DOI: 10.15468/dl.9vp95e
title: Occurrence Download

description: A dataset containing 72 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Parapaguridae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 72 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036977-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/ymz8nlrg
title: Traffic3

description: Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation.
DOI: 10.57702/94h5fufm
title: Solar-Energy4

description: The solar power production records in the year of 2006, which is sampled every 10 minutes from 137 PV plants in Alabama State.
DOI: 10.57702/up8x80d1
title: Electricity5

description: The electricity consumption in kWh was recorded every 15 minutes from 2012 to 2014, for n = 321 clients.
DOI: 10.57702/qeysvbyl
title: Exchange-Rate

description: The collection of the daily exchange rates of eight foreign countries including Australia, British, Canada, Switzerland, China, Japan, New Zealand and Singapore ranging from 1990 to 2016.
DOI: 10.57702/nfm22336
title: Maximum Likelihood Estimation for a Markov-Modulated Jump-Diﬀusion Model

description: The dataset is used to estimate the parameters of a Markov-Modulated Jump-Diﬀusion Model (MMJDM) for stock prices.
DOI: 10.57702/ckopkb24
title: Real Data

description: The dataset is used to estimate the parameters of a Markov-Modulated Jump-Diﬀusion Model (MMJDM) for stock prices.
DOI: 10.57702/f06lp1p6
title: Koopcon: A new approach towards smarter and less complex learning

description: The dataset condensation problem involves transforming a large-scale training set X into a smaller synthetic set X'.
DOI: 10.57702/w6vpcsvm
title: Conditional Diffusion Schrödinger Bridge

description: Conditional diffusion Schrödinger bridge for conditional simulation
DOI: 10.57702/3zdxqp44
title: UltraMNIST

description: UltraMNIST is a synthetic dataset generated by making use of the MNIST digits. For constructing an image, 3-5 digits are sampled such that the total sum of digits is less than 10.
DOI: 10.57702/6yq91969
title: PANDA

description: PANDA is a dataset of high-resolution histopathological images, and for this study, we consider a maximum image resolution of 4096 x 4096 pixels.
DOI: 10.57702/pnoh9vd7
title: BraTS 2020 Validation

description: The BraTS 2020 validation dataset contains the same type of MR images from 125 patients, without the ground truth annotations.
DOI: 10.57702/qi9iasdw
title: Street View

description: Street View is a large-scale dataset of 3D scenes, consisting of millions of images taken from street-level cameras.
DOI: 10.57702/r5pltb8a
title: GHuNeRF: Generalizable Human NeRF from a Monocular Video

description: GHuNeRF: Generalizable Human NeRF from a Monocular Video
DOI: 10.57702/x1vcc76y
title: Argoverse 2

description: The Argoverse 2 motion forecasting dataset contains 250,000 driving scenarios, each 11 seconds long. These scenarios cover 6 geographical regions and represent 763 total hours of driving.
DOI: 10.15468/dl.cs9tj2
title: Occurrence Download

description: A dataset containing 302 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Vespa soror Buysson, 1905)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 302 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036978-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/czrnd8kt
title: UCL-Dehaze

description: Real-world image dehazing via unsupervised contrastive learning
DOI: 10.57702/wz0nwdi6
title: Dex-NeRF: Using a Neural Radiance Field to Grasp Transparent Objects

description: Synthetic datasets of transparent objects for training NeRF models.
DOI: 10.57702/dxticmyu
title: MOFA-Video

description: MOFA-Video is a controllable image animation method that generates video from the given image using various additional controllable signals.
DOI: 10.57702/4w0nifdd
title: SadTalker

description: SadTalker is a dataset used for generating facial landmarks from audio.
DOI: 10.57702/1on2ty3l
title: WIDER-Test

description: Blind face restoration dataset
DOI: 10.57702/foey2g6q
title: Modified IEEE 33-bus, 69-bus, and 118-bus RDSs

description: The dataset used in the paper is a modified IEEE 33-bus, 69-bus, and 118-bus radial distribution systems.
DOI: 10.57702/r0mruhee
title: Thebe

description: The largest publicly available field fault dataset, Thebe, provides a critical public benchmark for research.
DOI: 10.57702/umg7hp8f
title: KartalOl dataset

description: A new dataset for iris segmentation and localization, including iris photos taken with two different smartphones (iPhone X and iPhone 11) in mixed illumination.
DOI: 10.57702/pg5u2p6i
title: Li et al. dataset

description: A deep-learning-based iris segmentation technique using a quicker R-CNN supplemented with six layers.
DOI: 10.57702/sx3g1qcl
title: Han et al. dataset

description: An efficient and robust iris segmentation algorithm using deep learning.
DOI: 10.57702/oqo5861n
title: Daugman dataset

description: A method for iris recognition using multi-algorithmic approaches.
DOI: 10.57702/xi9c8afj
title: PhysioNet/Computing in Cardiology Challenge 2021

description: Electrocardiogram (ECG) dataset used for cardiac irregularity classification
DOI: 10.57702/ibagqg8h
title: Open Access Database for ECG Rhythm and Morphology Abnormality Detection

description: ECG dataset used for evaluating algorithms for ECG rhythm and morphology abnormality detection
DOI: 10.57702/b2rmrk02
title: 12-lead ECG Database for Arrhythmia Research

description: ECG dataset used for arrhythmia research
DOI: 10.57702/q2bl6u0s
title: BEND: Bagging Deep Learning Training Based on Efficient Neural Network Diffusion

description: The paper proposes a Bagging Deep Learning Training Framework (BEND) based on efficient neural network diffusion.
DOI: 10.57702/sak7clwf
title: 15 Scenes

description: The dataset used in this paper is a benchmark dataset for image and video classification. It contains 15 scenes with 4485 images, and 102 classes with 9144 images. The dataset is used to evaluate the performance of the proposed dimensionality reduction approach.
DOI: 10.57702/p85y2bgr
title: Stargan v2: Diverse image synthesis for multiple domains

description: Stargan v2 dataset
DOI: 10.57702/idzqzca6
title: StableQ

description: StableQ: Enhancing Data-Scarce Quantization with Text-to-Image Data
DOI: 10.57702/a2zaouwx
title: LostNet: A smart way for lost and found

description: The dataset is used for lost and found image identification. It contains images of lost and found items, and the authors used it to train a deep learning model to identify the categories of the images.
DOI: 10.57702/k7ykxzuy
title: VOC

description: The dataset used in the paper is the VOC dataset, which is a dataset for object detection and segmentation.
DOI: 10.57702/j0razdeh
title: ALNSB

description: The dataset used in this paper is a collection of 51 seed images of lung nodules, which are used to train an autoencoder-based system to generate synthetic 3D lung nodule images.
DOI: 10.15468/dl.jrpxzd
title: Occurrence Download

description: A dataset containing 27022 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sagittidae",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 27022 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036979-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/itr6sbcm
title: ARUBA

description: Human Activity Recognition (HAR) has been the focus of research efforts due to its key role for different ambient assisted living (AAL) domains as well as the increasing demand for home automation and convenience services in daily activities.
DOI: 10.57702/r4egqbwa
title: MILAN

description: Human Activity Recognition (HAR) has been the focus of research efforts due to its key role for different ambient assisted living (AAL) domains as well as the increasing demand for home automation and convenience services in daily activities.
DOI: 10.57702/gbgarixy
title: Kubric

description: Neural radiance fields (NeRF) excel at synthesizing new views given multi-view, calibrated images of a static scene. When scenes include distractors, which are not persistent during image capture (moving objects, lighting variations, shadows), artifacts appear as view-dependent effects or 'ﬂoaters'.
DOI: 10.57702/o27n0ay1
title: Low-dose CT image denoising dataset

description: The dataset used for training and testing deep neural networks-based denoising models for CT imaging.
DOI: 10.57702/vr44w0x1
title: Mushroom Species Classification Dataset

description: The dataset used in this paper for mushroom classification, containing images of 100 distinct species of mushrooms.
DOI: 10.57702/8rs7boqv
title: SMU-Net

description: The SMU-Net dataset is not explicitly mentioned in the paper, but it is used as a benchmark for the proposed method.
DOI: 10.57702/2ksrt7q7
title: Optimal Flow Matching

description: The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a 2D setup to illustrate the proof-of-concept of their Optimal Flow Matching approach.
DOI: 10.57702/jl9172mj
title: Protein Generation Dataset

description: The dataset used in the paper is a protein generation dataset, which includes proteins with features and edge features.
DOI: 10.57702/0huno9fz
title: Waxman Random Graph Dataset

description: The dataset used in the paper is a Waxman random graph dataset, which includes graphs with features and edge features.
DOI: 10.57702/dagh904m
title: You Only Look Clusters (YOLC)

description: Detecting objects from aerial images poses significant challenges due to the following factors: 1) Aerial images typically have very large sizes, generally with millions or even hundreds of millions of pixels, while computational resources are limited. 2) Small object size leads to insufficient information for effective detection. 3) Non-uniform object distribution leads to computational resource wastage.
DOI: 10.57702/whco88k9
title: Nested Hierarchical Transformer

description: The dataset used in the paper is not explicitly mentioned, but it is implied to be ImageNet and CIFAR-10/100.
DOI: 10.57702/yl77riz1
title: RIGA+ dataset

description: The RIGA+ dataset is a multi-domain joint optic disc (OD) / optic cup (OC) segmentation dataset annotated by six ophthalmologists.
DOI: 10.57702/hl4gsxh9
title: CelebA-HQ-128

description: CelebA-HQ-128
DOI: 10.57702/rbloe1r8
title: PR-MCS: Perturbation Robust Metric for Multilingual Image Captioning

description: PR-MCS: Perturbation Robust Metric for Multilingual Image Captioning
DOI: 10.57702/bcz7cdsz
title: UMIC: An unreferenced metric for image captioning via contrastive learning

description: UMIC: An unreferenced metric for image captioning via contrastive learning
DOI: 10.57702/mf6v4nl1
title: BiHMP-GAN: Bidirectional 3D Human Motion Prediction GAN

description: Human motion prediction model has applications in various fields of computer vision. Without taking into account the inherent stochasticity in the prediction of future pose dynamics, methods often converge to a deterministic undesired mean of multiple probable outcomes.
DOI: 10.57702/6ak8eo4y
title: ML4H Findings Track Collection: Machine Learning for Health (ML4H) 2023

description: A synthetic dataset for training a family of Reinforcement Learning (RL) methods to build explainable pathways for the differential diagnosis of anemia, as a primary use case.
DOI: 10.57702/caruc60c
title: Discovery of Clinical Pathway Patterns from Event Logs Using Probabilistic Topic Models

description: A dataset for discovering clinical pathway patterns from event logs using probabilistic topic models.
DOI: 10.57702/0p0e2knp
title: BraTS 2020: self-ensembled, deeply-supervised 3D U-Net CNNs

description: Brain tumor segmentation is a critical task for patient’s disease management. In order to automate and standardize this task, we trained multiple U-net like neural networks, mainly with deep super-vision and stochastic weight averaging, on the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2020 training dataset.
DOI: 10.57702/tygtgurx
title: EMNIST and Google Fonts datasets

description: The EMNIST dataset comprises 27,600 capital letter images (about 1,062 for each of 26 classes), and the Google Fonts dataset comprises 67,600 capital letter images (2,600 different fonts for each letter class).
DOI: 10.57702/i4r13le3
title: Recipe1M and CUB datasets

description: Recipe1M and CUB datasets for text-to-image synthesis
DOI: 10.57702/5j34f3vm
title: AGC System Traffic Data

description: The dataset used in this paper is the AGC system traffic data, which is used for anomaly detection in automatic generation control systems.
DOI: 10.57702/zrmmh42h
title: Yelp 2013 Document

description: The dataset used in the paper is a collection of text sequences for text classification tasks.
DOI: 10.57702/u23zonpn
title: Yelp 2014 Document

description: The dataset used in the paper is a collection of text sequences for text classification tasks.
DOI: 10.15468/dl.4fs3as
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-13.84164 -37.9507,-10.84967 -37.9507,-10.84967 -36.72069,-13.84164 -36.72069,-13.84164 -37.9507))",
 "TaxonKey is Arachnida"
 ]
}

 The dataset includes 6 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036980-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/f9iiiccc
title: IMDB Document

description: The dataset used in the paper is a collection of text sequences for text classification tasks.
DOI: 10.57702/eswslz6c
title: Dirichlet-Survival Process: Scalable Inference of Topic-Dependent Diﬀusion Networks

description: The Houston model jointly considers all three features: documents' content, time of publication relative to other publications, and position of the spreader in the network.
DOI: 10.57702/b5rfwtai
title: Arbitrary Style Transfer with Structure Enhancement by Combining the Global and Local Loss

description: Arbitrary style transfer generates an artistic image which combines the structure of a content image and the artistic style of the artwork by using only one trained network.