cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57702/f0obzw83
title: DFU Infection Classification Dataset

description: The DFU infection classification dataset used in this paper, comprising 2,946 augmented patches with infection and 2,946 augmented patches without infection.
DOI: 10.57702/b5qlxu10
title: Generalization in Deep Reinforcement Learning for Robotic Navigation by Reward Shaping

description: A novel reward function for reinforcement learning and a Soft Actor-Critic algorithm to train a DRL policy in the context of local navigation for autonomous mobile robots in unknown cluttered environments.
DOI: 10.57702/sx8f8rfp
title: WMT En-De, WMT En-Fr, and WMT En-Ro

description: The WMT En-De, WMT En-Fr, and WMT En-Ro translation tasks.
DOI: 10.57702/2g0rb1tf
title: Autoencoders and Generative Adversarial Networks for Imbalanced Sequence Classification

description: Generative Adversarial Networks (GANs) have been used in many different applications to generate realistic synthetic data. We introduce a novel GAN with Autoencoder (GAN-AE) architecture to generate synthetic samples for variable length, multi-feature sequence datasets.
DOI: 10.57702/tq0zp0i3
title: SMOTE: Synthetic Minority Over-Sampling Technique

description: SMOTE: synthetic minority over-sampling technique.
DOI: 10.15468/dl.nd7cv6
title: Occurrence Download

description: A dataset containing 226 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 tenuissima Trin.)"
 ]
}

 The dataset includes 226 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014103-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/1grds9dp
title: Synapse multi-organ dataset

description: The Synapse multi-organ dataset is a collection of 30 abdominal CT scans with corresponding segmentation masks.
DOI: 10.57702/x9djcwh1
title: Deep Image Matting

description: The Deep Image Matting dataset contains 431 training images with the corresponding alpha maps and the foreground images.
DOI: 10.57702/a9pez1wo
title: ATLAS Dione

description: ATLAS Dione is a dataset for RAS video understanding, providing video data of ten surgeons performing six different surgical tasks on the daVinci Surgical System (dVSS R(cid:13)) with annotations of robotic tools per frame.
DOI: 10.57702/r45akb2q
title: LJSpeech-1.1

description: The LJSpeech-1.1 dataset is a large-scale speech dataset containing approximately 24 hours of single-speaker speech recorded at 22 050 Hz.
DOI: 10.57702/qhnv043v
title: HandDiffuse12.5M

description: HandDiffuse12.5M dataset consists of temporal sequences with strong two-hand interactions. It covers interacting hand motions in random and complex poses, daily communications, finger dances, and Chinese daily sign language.
DOI: 10.57702/framsfl5
title: RenderIH

description: RenderIH dataset is a large-scale synthetic dataset for 3D interacting hand pose estimation from a single RGB image.
DOI: 10.57702/5uye7bg5
title: InterHand2.6M

description: The InterHand2.6M dataset contains 366K training samples, 110K validation samples, and 261K test samples. It is the only interacting two-hand dataset with dense shape annotations.
DOI: 10.15468/dl.97832d
title: Occurrence Download

description: A dataset containing 4140 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pyrus pyrifolia (Burm.fil.) Nakai"
 ]
}

 The dataset includes 4140 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014104-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/b5ys6ihk
title: Re:InterHand

description: Re:InterHand dataset is a large-scale dataset for 3D interacting hand pose estimation from a single RGB image.
DOI: 10.57702/km8iuikz
title: CharacterTrajectories Dataset

description: The CharacterTrajectories dataset is part of the UEA time series classification archive.
DOI: 10.57702/ta2ci6v4
title: Speech Commands Dataset

description: The dataset used for training the keyword spotting model is the ESC: Dataset for Environmental Sound Classification, and the Speech Commands Dataset.
DOI: 10.15468/dl.ucs9jy
title: Occurrence Download

description: A dataset containing 4609 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Prunus serrulata Lindl."
 ]
}

 The dataset includes 4609 records from 227 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014105-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/bvskrsw3
title: Lattice Proteins

description: Lattice-protein (LP) models were introduced in the 90s to investigate the properties of proteins, particularly how their structure depend on their sequences. They were recently used to benchmark graphical models inferred from sequence data.
DOI: 10.57702/9wysn4hc
title: Improving accuracy and speeding up Document Image Classiﬁcation

description: Document digitization has become a common practice in a wide variety of industries that deal with vast amounts of archives. Document classiﬁcation is a task to face when trying to automate their document processes, but high intra-class and low inter-class variability between documents have made this a challenging problem.
DOI: 10.57702/z64bvxse
title: RVL-CDIP (Ryerson Vision Lab Complex Document Information Processing)

description: Document digitization has become a common practice in a wide variety of industries that deal with vast amounts of archives. Document classiﬁcation is a task to face when trying to automate their document processes, but high intra-class and low inter-class variability between documents have made this a challenging problem.
DOI: 10.57702/bz1s1n6j
title: Tobacco3482

description: Document digitization has become a common practice in a wide variety of industries that deal with vast amounts of archives. Document classiﬁcation is a task to face when trying to automate their document processes, but high intra-class and low inter-class variability between documents have made this a challenging problem.
DOI: 10.57702/3a3oo114
title: LAION-Improved-Aesthetics (v1.2)

description: The LAION-Improved-Aesthetics (v1.2) dataset used for training the Stable Diffusion model, which includes images with captions.
DOI: 10.5284/1124879
title: Data from an Archaeological Evaluation at Langarth Garden Village, Langarth, Truro, Cornwall, 2021-2022

description: This digital archive comprises images and site records from the results of an archaeological evaluation that was carried out in May 2021 and May 2022, by South West Archaeology Ltd. (SWARCH) for a mixed use development at Langarth Garden Village, Langarth, Truro, Cornwall. The fieldwork was carried out in two phases.
DOI: 10.57702/lkp23okf
title: Transparent Tableware Dataset

description: The Transparent Tableware Dataset (TTD) is a dataset made available with this paper that includes 600 stereo images of real scenes with some objects positioned in the scene, including 5 transparent objects.
DOI: 10.57702/igc8xjka
title: Transparent Object Dataset

description: The TOD dataset is a public stereo object pose estimation dataset that includes about 45,000 stereo images of 15 different objects, along with the ground truth segmentation masks for the left camera, pose annotations, and depth maps.
DOI: 10.57702/yh5lsc9d
title: COVID-19 Lung Infections in Chest CT volumes

description: The dataset used in this work consists of 29 CT volumes from two different sources of lung infection data, resulting from COVID-19.
DOI: 10.57702/72bxbg48
title: Jun et al. COVID-19 Lung Infections in Chest CT volumes

description: The dataset used in this work consists of 20 volumes from Jun et al. consisting of infections labelled by two radiologists and verified by another experienced radiologist.
DOI: 10.57702/4nhg3iiw
title: STPDnet: Spatial-Temporal Convolutional Primal Dual Network for Dynamic PET Image Reconstruction

description: Dynamic PET image reconstruction dataset
DOI: 10.57702/2yv6v5m7
title: Alpaca-52K

description: The Alpaca-52K instruction-following dataset is a large-scale dataset containing instruction-following tasks.
DOI: 10.57702/vu1ao0x5
title: Ship Discrimination Dataset

description: The ship discrimination dataset contains SAR images of ships and non-ships
DOI: 10.57702/uyxrx1df
title: VOLTA: Improving Generative Diversity by Variational Mutual Information Maximizing Autoencoder

description: The dataset used in the paper is not explicitly described, but it is mentioned that the authors used six datasets from three different NLG tasks.
DOI: 10.6084/m9.figshare.27951465
title: Raw data

description: Global changes are forcing forest management towards more resilient and more structurally complex forests. Hereby creating a more attractive habitat for their associated biodiversity. Measuring this forest structural complexity and how it relates to associated biodiversity is however challenging. Here, we used the structural complexity index (SCI), designed for forests managers to quick and easily assess structural complexity. Studies comparing the predictive value of such index with taxonomic biodiversity monitoring are rare. In this study, we focus on wild pollinators, which could potentially benefit from this shift towards more structurally complex forests. We used elevated pan traps in 19 forest plots varying in structural complexity and dominant tree species to answer following questions. First, we investigated how predictive the SCI is for wild bee and syrphid abundance and diversity. Second, we studied the communities and how these relate to the SCI. We found that the SCI was not predictive for both the abundance and diversity. We found some tree species identity effects for abundance and diversity, stressing the importance of maintaining multiple tree species. However, no differences between wild pollinator communities of forest types and SCI-levels were observed. Our results show that a tool such as the SCI, which allows forest managers to quickly assess the potential of forest stands to accommodate biodiversity, is not necessarily predictive for each taxonomic group. However, combining collection methods across multiple years and taxonomic groups, should provide additional insights for the total assessment of the predictive value of the SCI for pollinators in forests.
DOI: 10.6084/m9.figshare.27951465.v1
title: Raw data

description: Global changes are forcing forest management towards more resilient and more structurally complex forests. Hereby creating a more attractive habitat for their associated biodiversity. Measuring this forest structural complexity and how it relates to associated biodiversity is however challenging. Here, we used the structural complexity index (SCI), designed for forests managers to quick and easily assess structural complexity. Studies comparing the predictive value of such index with taxonomic biodiversity monitoring are rare. In this study, we focus on wild pollinators, which could potentially benefit from this shift towards more structurally complex forests. We used elevated pan traps in 19 forest plots varying in structural complexity and dominant tree species to answer following questions. First, we investigated how predictive the SCI is for wild bee and syrphid abundance and diversity. Second, we studied the communities and how these relate to the SCI. We found that the SCI was not predictive for both the abundance and diversity. We found some tree species identity effects for abundance and diversity, stressing the importance of maintaining multiple tree species. However, no differences between wild pollinator communities of forest types and SCI-levels were observed. Our results show that a tool such as the SCI, which allows forest managers to quickly assess the potential of forest stands to accommodate biodiversity, is not necessarily predictive for each taxonomic group. However, combining collection methods across multiple years and taxonomic groups, should provide additional insights for the total assessment of the predictive value of the SCI for pollinators in forests.
DOI: 10.57702/a2w4rqfj
title: YELP

description: The YELP dataset is used for language modeling.
DOI: 10.57702/0tts4mxj
title: Deep Q-Networks for Intelligent Transportation Systems

description: The dataset is used for Deep Q-Networks (DQN) to optimize real-time trafﬁc light control policies in emerging large-scale Intelligent Transportation Systems.
DOI: 10.57702/bhno6kfn
title: WMT18 news dataset

description: The WMT18 news dataset is used for segment-level quality estimation of machine translation.
DOI: 10.57702/l19mhkzi
title: Multimodal Spatiotemporal Graph-Transformer

description: Multimodal Spatiotemporal Graph-Transformer for Hospital Readmission Prediction
DOI: 10.57702/75t1o3h9
title: Monotone Tree-Based GAMI Models by Adapting XGBoost

description: Simulated datasets are used to demonstrate the behaviors of mono-GAMI-Tree and EBM, both of which use piecewise constant fits.
DOI: 10.57702/qyzllr98
title: Real-time 3D Shape Instantiation for Partially-deployed Stent Segment

description: A 3D shape instantiation framework for partially-deployed stent segment from a single intra-operative 2D fluoroscopic image.
DOI: 10.57702/xgou2iy0
title: 3D Stent and Marker Dataset

description: A dataset of 3D stents and 3D customized markers for training and testing the 3D shape instantiation framework.
DOI: 10.57702/a7qth18x
title: ViSTRA2 Dataset

description: The dataset used in the paper is a collection of video sequences with varying resolutions and bit depths, used for training and testing the proposed video compression framework.
DOI: 10.57702/24smssy2
title: JVET Common Test Conditions

description: The dataset used in the paper is a collection of video sequences with varying resolutions and bit depths, used for training and testing the proposed video compression framework.
DOI: 10.57702/o5mvhyj6
title: 3DMatch

description: The 3DMatch [26] is a well-known indoor registration dataset of 62 scenes captured by RGBD sensor.
DOI: 10.57702/2h52t1ql
title: Cart-Pole Problem

description: The cart-pole problem is a classic control problem in robotics and control theory. It is a continuous control problem where the goal is to keep the pole upright by applying a force to the cart.
DOI: 10.57702/y67ipqap
title: CEDAR, Bengali, and Hindi datasets

description: Three public datasets, namely CEDAR, Bengali, and Hindi, which include genuine (Human Genuine) and forgery (Human Forged) signatures.
DOI: 10.57702/h0a3apbm
title: Elon Musk Tweets Dataset

description: The Elon Musk tweets dataset is a collection of tweets published by Elon Musk between 2017 and 2022.
DOI: 10.57702/j9ekph80
title: Adaptive Multi-head Contrastive Learning

description: Adaptive Multi-head Contrastive Learning (AMCL) framework, which tackles intra- and inter-sample similarity and adaptive temperature mechanism re-weighting each similarity pair.
DOI: 10.57702/0107shk5
title: MovieLens Latest, MovieLens 1m, MovieLens 10m, Yelp

description: The dataset used in the paper is MovieLens Latest, MovieLens 1m, MovieLens 10m, and Yelp.
DOI: 10.57702/44gzcgj4
title: Cloud-Assisted Collaborative Road Information Discovery with Gaussian Process

description: A novel cloud-based collaborative road information discovery framework using multiple heterogeneous vehicles was developed. Gaussian process was used to crowd-source individual estimates, which was then used as pseudo-measurements for future vehicles to enhance its local measurements.
DOI: 10.57702/ks9yom3k
title: Multimodal Hate Speech Detection in Bengali

description: Multimodal hate speech detection dataset for Bengali language
DOI: 10.57702/cka27dkb
title: MIT1003 dataset

description: MIT1003 dataset contains 1003 natural images with corresponding saliency maps and scanpaths.
DOI: 10.15468/dl.ve74g6
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((121 42,128 42,128 49,121 49,121 42))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Sibirionetta formosa (Georgi, 1775)",
 "Year 2000-2024"
 ]
}

 The dataset includes 10 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014106-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/nyl2igap
title: Synthetic Data Generation for Variational Autoencoders

description: Synthetic swaption cubes generated from existing ones
DOI: 10.57702/fxtwfk6l
title: Track Anything Rapter (TAR)

description: The Track Anything Rapter (TAR) project utilizes state-of-the-art pre-trained models to accurately detect and track target objects through multimodal queries.
DOI: 10.57702/8yvqw4uk
title: Solar radiation

description: The dataset is used for functional linear regression models, where the coeﬃcient function is shrunk towards a data-driven shape template γ.
DOI: 10.57702/v2lnsh84
title: London bike sharing

description: The dataset is used for functional linear regression models, where the coeﬃcient function is shrunk towards a data-driven shape template γ.
DOI: 10.57702/ojorrtub
title: MS COCO dataset for object detection

description: The MS COCO dataset is a task for object detection.
DOI: 10.57702/33iovo4k
title: Office dataset

description: Office dataset consists of 31 categories and contains around 4,700 images across three domains, namely Amazon(A), DSLR(D) and Webcam(W).
DOI: 10.57702/icdsgj6r
title: VisDA dataset

description: VisDA dataset consists of 12 categories and contains around 150,000 synthetic and 50,000 real-world images in the source and target domains, respectively.
DOI: 10.57702/sjqdbsk9
title: ActivityNet v1.2

description: Weakly-Supervised Temporal Action Localization (WSTAL) aims to localize actions in untrimmed videos with only video-level labels.
DOI: 10.57702/csu99wqe
title: Thumos14

description: Video moment retrieval task, which only retrieves the video clip with certain action given a query.
DOI: 10.57702/3n1vs281
title: Head and Neck FDG PET-CT TCIA Dataset

description: A dataset used for outcome prediction in head and neck cancer
DOI: 10.57702/wljmgw0a
title: DTU, BlendMVS, and H3DS datasets

description: The DTU, BlendMVS, and H3DS datasets are used for evaluating the performance of the VQ-NeRF method.
DOI: 10.57702/s3zwonz0
title: Transformer-Based Attention Networks for Continuous Pixel-Wise Prediction

description: The proposed TransDepth framework for pixel-wise prediction problems involving continuous labels.
DOI: 10.6084/m9.figshare.27074174
title: Preclinical characterization of a water-soluble low-impact ampakine prodrug, CX1942 and its active moiety, CX1763

description: <b>Aim:</b> AMPA-glutamate receptor (AMPAR) dysfunction mediates multiple neurological/neuropsychiatric disorders. Ampakines bind AMPARs and allosterically enhance glutamate-elicited currents. This report describes the activity of the water-soluble ampakine CX1942 prodrug and the active moiety CX1763. <b>Results:</b> CX1763 and CX1942 enhance synaptic transmission in hippocampi of rats. CX1763 increases attention in the 5CSRTT in rats and reduces amphetamine-induced hyperactivity in mice. CX1942 potently reverses opioid-induced respiratory depression in rats. CX1942/CX1763 was effective at 2.5–10 mg/kg. CX1763 lacked epileptogenicity up to 1500 mg/kg in rats. <b>Conclusion:</b> These data document that CX1942 and CX1763 are active and without prominent side effects in multiple pre-clinical assays. CX1942 could serve as a prodrug for CX1763 with the advantage of high water solubility as in an intravenous formulation. The water-soluble glycine ester pro-drug of CX1763, CX1942 is potent and active against alfentanil-induced respiratory depression <i>in vivo</i> CX1942 and CX1763 produce a durable increase in hippocampal EPSP <i>in vivo</i> CX1763 increases metrics of attention in rodents while reducing hyperactivity associated with amphetamine, indicating multiple potential benefits for ADHD treatment CX1763/CX1942 is therapeutically active at doses of 2.5–10 mg/kg and CX1763 lacks epileptic and fatal toxicities up to 1500 mg/kg, demonstrating a notable safety margin, justifying further preclinical and clinical explorations
DOI: 10.6084/m9.figshare.27074174.v1
title: Preclinical characterization of a water-soluble low-impact ampakine prodrug, CX1942 and its active moiety, CX1763

description: <b>Aim:</b> AMPA-glutamate receptor (AMPAR) dysfunction mediates multiple neurological/neuropsychiatric disorders. Ampakines bind AMPARs and allosterically enhance glutamate-elicited currents. This report describes the activity of the water-soluble ampakine CX1942 prodrug and the active moiety CX1763. <b>Results:</b> CX1763 and CX1942 enhance synaptic transmission in hippocampi of rats. CX1763 increases attention in the 5CSRTT in rats and reduces amphetamine-induced hyperactivity in mice. CX1942 potently reverses opioid-induced respiratory depression in rats. CX1942/CX1763 was effective at 2.5–10 mg/kg. CX1763 lacked epileptogenicity up to 1500 mg/kg in rats. <b>Conclusion:</b> These data document that CX1942 and CX1763 are active and without prominent side effects in multiple pre-clinical assays. CX1942 could serve as a prodrug for CX1763 with the advantage of high water solubility as in an intravenous formulation. The water-soluble glycine ester pro-drug of CX1763, CX1942 is potent and active against alfentanil-induced respiratory depression <i>in vivo</i> CX1942 and CX1763 produce a durable increase in hippocampal EPSP <i>in vivo</i> CX1763 increases metrics of attention in rodents while reducing hyperactivity associated with amphetamine, indicating multiple potential benefits for ADHD treatment CX1763/CX1942 is therapeutically active at doses of 2.5–10 mg/kg and CX1763 lacks epileptic and fatal toxicities up to 1500 mg/kg, demonstrating a notable safety margin, justifying further preclinical and clinical explorations
DOI: 10.57702/ugtdrw8i
title: Comics, Paintings, and ChestX

description: The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the CLIP model and the Comics, Paintings, and ChestX datasets.
DOI: 10.57702/riww7pt5
title: Robustiﬁcation of Segmentation Models Against Adversarial Perturbations In Medical Imaging

description: A defense framework for segmentation models against adversarial attacks in medical imaging
DOI: 10.57702/gyohw0iy
title: Amazon-Beauty dataset

description: The Amazon-Beauty dataset is a sub-dataset from Amazon Product Reviews 3, which records large crawls of user reviews and product metadata.
DOI: 10.57702/qbptxtve
title: Amazon-Appliances dataset

description: The Amazon-Appliances dataset is a sub-dataset from Amazon Product Reviews 3, which records large crawls of user reviews and product metadata.
DOI: 10.57702/aw4m6rby
title: R2U-Net: A Deep Learning Model for Medical Image Segmentation

description: The R2U-Net is a deep learning model for medical image segmentation that combines U-Net, ResNet, and recurrent neural network (RCNN).
DOI: 10.57702/9nv7us2k
title: 3D Unet: A Deep Learning Model for Medical Image Segmentation

description: The 3D Unet is a deep learning model for medical image segmentation that uses a U-Net architecture.
DOI: 10.57702/obon8yms
title: V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

description: The V-Net is a deep learning model for medical image segmentation that uses a U-Net architecture.
DOI: 10.57702/p8hx2ah8
title: Visual Object Tracking Benchmark

description: The OTB2013 and OTB2015 datasets contain video sequences for visual object tracking.