cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.27935040
title: Supporting data of "<b>The Diverse Phenotypic and Mutational Landscape Induced by Fluoroquinolone Treatment</b>" article

description: This data supports the paper "<b>The Diverse Phenotypic and Mutational Landscape Induced by Fluoroquinolone Treatment</b>"
DOI: 10.57702/r68bvyw5
title: PoetryDiffusion: Towards Jointly Semantic and Metrical Manipulation in Poetry Generation

description: Poetry generation dataset for Sonnet and SongCi poetry
DOI: 10.57702/s7n9lypk
title: Keystroke Dynamics for User Authentication

description: Keystroke dynamics dataset for user authentication
DOI: 10.57702/3ahwg2lx
title: FairFace dataset

description: The FairFace dataset is a balanced dataset for face attribute classification, focusing on gender, ethnicity, and age.
DOI: 10.57702/f8gcqp13
title: DIV2K+Flickr2K dataset

description: Dataset for single image super-resolution
DOI: 10.57702/gqmt7i52
title: Flickr2K dataset

description: The Flickr2K dataset is a low-resolution image dataset used for image super-resolution tasks.
DOI: 10.57702/pu315jm0
title: Building Efﬁcient Deep Neural Networks with Unitary Group Convolutions

description: Unitary group convolutions (UGConvs) are a building block for neural networks that combines a group convolution with unitary transforms in feature space.
DOI: 10.57702/gj4z94kn
title: ShufﬂeNet: An Extremely Efﬁcient Convolutional Neural Network for Mobile Devices

description: ShufﬂeNet is an extremely efficient convolutional neural network for mobile devices.
DOI: 10.57702/yiqxsvrm
title: CirCNN: Accelerating and Compressing Deep Neural Networks using Block-Circulant Matrices

description: CirCNN is a neural network architecture that uses block-circulant matrices to reduce the number of parameters and computations.
DOI: 10.57702/znjcgqn3
title: Low-Resolution Self-Attention for Semantic Segmentation

description: Semantic segmentation tasks naturally require high-resolution information for pixel-wise segmentation and global context information for class prediction.
DOI: 10.57702/kol4j6tr
title: CORD dataset

description: CORD dataset contains questions answerable using Wikidata as the knowledge graph, focusing on questions with a single entity and relation.
DOI: 10.57702/gnn9mwyn
title: FUNSD dataset

description: FUNSD dataset contains questions answerable using Wikidata as the knowledge graph, focusing on questions with a single entity and relation.
DOI: 10.57702/d7nph8e5
title: Custom Simulator Dataset

description: The dataset used in the paper is a custom-built simulator dataset, which is used to train and test the neural radiance field (NeRF) model.
DOI: 10.57702/w88u67db
title: Prototypical Alignment, Uniformity and Correlation

description: Contrastive self-supervised learning (CSL) with a prototypical regularization has been introduced in learning meaningful representations for downstream tasks that require strong semantic information.
DOI: 10.57702/j2z390lf
title: Contrastive multiview coding

description: Contrastive multiview coding.
DOI: 10.57702/ykro53mr
title: IN-MIO COMPASS Ocean general circulation model

description: The dataset contains daily temperature and salinity fields taken from the IN-MIO COMPASS global ocean circulation model for 3m and 45m depth near the Svalbard group of islands from 2 Jan 2004 to 31 Dec 2020.
DOI: 10.57702/4e8k17m1
title: Synchrotron Radiation CT Reconstruction

description: Synchrotron radiation CT reconstruction dataset
DOI: 10.57702/95it84c1
title: Tomopy

description: Tomopy dataset
DOI: 10.57702/3d39451c
title: End-to-End User Behavior Retrieval in Click-Through Rate Prediction Model

description: Click-Through Rate (CTR) prediction is one of the core tasks in recommender systems (RS). It predicts a personalized click probability for each user-item pair.
DOI: 10.57702/lrcolf9z
title: Camelyon16 dataset

description: Whole Slide Image (WSI) analysis is a powerful method to facilitate the diagnosis of cancer in tissue samples. Automating this diagnosis poses various issues, most notably caused by the immense image resolution and limited annotations.
DOI: 10.57702/ntftf4z4
title: United Nations Parallel Corpus

description: High-quality human translations from books, leveraging the induction bias that high-quality human translations are superior to machine-generated translations.
DOI: 10.57702/ew00yctm
title: EncodeNet: A Framework for Boosting DNN Accuracy

description: Image classification is a fundamental task in computer vision, and the quest to enhance DNN accuracy without inflating model size or latency remains a pressing concern.
DOI: 10.57702/souwhdct
title: ImageNet classiﬁcation dataset

description: The dataset used for image classiﬁcation and semantic image segmentation.
DOI: 10.57702/i5758bop
title: PASCAL Context

description: The PASCAL Context dataset is a benchmark for multi-task learning in computer vision. It contains 10103 images with 5 tasks: semantic segmentation, human body part segmentation, surface normal estimation, saliency estimation, and edge detection.
DOI: 10.57702/j437ki3g
title: SARS-CoV-2 Complete Genomes

description: The dataset used for training and testing the quantum style-based GAN model for predicting spike protein variation structure of COVID-19 epidemic strains.
DOI: 10.57702/5ve2iyij
title: Codeforces

description: The Codeforces dataset contains solutions to competitive programming problems.
DOI: 10.57702/8u1buuvc
title: Encoder-Decoder Neural Architecture Optimization for Keyword Spotting

description: Keyword spotting aims to identify speciﬁc keyword audio ut-terances. In recent years, deep convolutional neural networks have been widely utilized in keyword spotting systems.
DOI: 10.57702/jldcugl8
title: Speech commands: A dataset for limited-vocabulary speech recognition

description: Speech commands: A dataset for limited-vocabulary speech recognition.
DOI: 10.57702/z4mxhe84
title: Gowalla, Yelp, and ML-1M

description: The dataset used in this paper is Gowalla, Yelp, and ML-1M. Gowalla is a social media platform with 210,537 users and 100,000 items. Yelp is a review website with 1,000,209 users and 731,672 items. ML-1M is a movie rating dataset with 6,040 users and 25,677 items. The dataset is used for recommendation systems.
DOI: 10.57702/99uwtm7u
title: GazeHOI

description: The GazeHOI dataset is a comprehensive resource for studying the complex interaction between human hands, objects, and gaze.
DOI: 10.57702/mn5vb91w
title: The 2021 Multimodal Brain Tumor Segmentation Challenge (BraTS21) dataset

description: The 2021 Multimodal Brain Tumor Segmentation Challenge (BraTS21) dataset
DOI: 10.57702/vd79woi6
title: OCT-ML: A Multi-Label OCT Dataset for Retinal Disease Classification

description: The OCT-ML dataset is a multi-label OCT dataset consisting of 1435 samples from 369 eyes of 203 patients considering multiple diseases.
DOI: 10.57702/03ywjpr9
title: Fundus Dataset

description: The Fundus dataset is a public fundus dataset used for evaluating the performance of the GeCA model.
DOI: 10.57702/edh1ghi0
title: GUH dataset

description: The dataset used in this study consists of breathing signals from 21 patients, with 15 of them obtained from the open-access database recorded at Georgetown University Hospital and the remaining 6 from Erasmus MC (Rotterdam, Netherlands).
DOI: 10.57702/2175uo6x
title: EMC dataset

description: The dataset used in this study consists of breathing signals from 6 patients, with amplitudes in the range (0.5,2) mm.
DOI: 10.57702/b8q4cuu5
title: OD/OC segmentation dataset

description: The dataset used for the OD/OC segmentation task and the polyp segmentation task.
DOI: 10.57702/cp7gj2wd
title: Preparing a collection of radiology examinations for distribution and retrieval

description: Preparing a collection of radiology examinations for distribution and retrieval.
DOI: 10.5281/zenodo.14219279
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Erich Werdermann, http://www.wikidata.org/entity/Q77133. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q77133
DOI: 10.5281/zenodo.8121499
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Erich Werdermann, http://www.wikidata.org/entity/Q77133. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q77133
DOI: 10.5281/zenodo.14262902
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Erich Werdermann, http://www.wikidata.org/entity/Q77133. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q77133
DOI: 10.5281/zenodo.8121498
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Erich Werdermann, http://www.wikidata.org/entity/Q77133. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q77133
DOI: 10.57702/90sb3sbz
title: Emotion-Oriented Behavior Model Using Deep Learning

description: The proposed model predicts the agent's emotion against each interaction with a human or against events to make it more cognitive and socially believable.
DOI: 10.57702/u4gs34pg
title: National Research Council (NRC)-Tweet Emotion Intensity Dataset

description: The dataset consists of published datasets from available sources containing labelled sentences of natural language (English) with eight emotions.
DOI: 10.57702/fjzr6pyz
title: Jan9-2012-tweets-clean.txt

description: The dataset consists of published datasets from available sources containing labelled sentences of natural language (English) with eight emotions.
DOI: 10.5281/zenodo.14262904
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Domenico Vandelli, http://www.wikidata.org/entity/Q1445443. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q1445443
DOI: 10.5281/zenodo.8312311
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Domenico Vandelli, http://www.wikidata.org/entity/Q1445443. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q1445443
DOI: 10.5281/zenodo.8312312
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Domenico Vandelli, http://www.wikidata.org/entity/Q1445443. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q1445443
DOI: 10.57702/4mk93f83
title: Multi-party Goal Tracking with LLMs: Comparing Pre-training, Fine-tuning, and Prompt Engineering

description: A dataset of 29 multi-party conversations between patients, their companions, and a social robot in a hospital.
DOI: 10.57702/onplof4l
title: Chest X-Ray8

description: The Chest X-Ray8 dataset is used to validate the performance of the proposed framework. The dataset contains 112,120 frontal view X-ray images of 32,717 unique patients.
DOI: 10.57702/u35zw2rn
title: MSDU-net: A Multi-Scale Dilated U-net for Blur Detection

description: Blur detection is the separation of blurred and clear regions of an image, which is an important and challenging task in computer vision. In this work, we regard blur detection as an image segmentation problem.
DOI: 10.57702/n8yw79u8
title: DUT Defocus Blur Detection Dataset

description: DUT is a new defocus blur detection dataset which consists of 500 images as the test set and 600 images as the train set.
DOI: 10.57702/1kh2fcxh
title: UCF101: A Dataset of 101 Human Actions Classes from Videos in the Wild

description: The authors used the UCF101, HMDB51, and Diving48 datasets to evaluate the performance of their proposed algorithm.
DOI: 10.5281/zenodo.14004468
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Ernst Heinrich Georg Ule, http://www.wikidata.org/entity/Q72701. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q72701
DOI: 10.5281/zenodo.14262907
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Ernst Heinrich Georg Ule, http://www.wikidata.org/entity/Q72701. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q72701
DOI: 10.5281/zenodo.8121607
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Ernst Heinrich Georg Ule, http://www.wikidata.org/entity/Q72701. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q72701
DOI: 10.5281/zenodo.8121608
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Ernst Heinrich Georg Ule, http://www.wikidata.org/entity/Q72701. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q72701
DOI: 10.57702/3oy40srt
title: ResNet20 and VGG16

description: The dataset used in this paper is ResNet20 and VGG16.
DOI: 10.57702/a5lqx57y
title: POP909

description: The POP909 dataset is a pop song dataset of 909 MIDI pieces containing lead melodies, secondary melodies, piano accompaniment tracks, key signatures, and chord annotations.
DOI: 10.57702/4v7urrwk
title: CADIS

description: A dataset for surgical RGB-image segmentation.
DOI: 10.57702/9hfuv91z
title: AﬀectNet

description: The AﬀectNet dataset is a facial expression dataset, consisting of images of faces with emotional expressions.
DOI: 10.57702/o7wjk1re
title: Connectionist Temporal Classification

description: The Connectionist Temporal Classification dataset is a speech emotion recognition dataset, consisting of audio recordings of speech.
DOI: 10.57702/cdgeyz1c
title: Ted Talks

description: The Ted Talks dataset is a speaker recognition dataset, consisting of audio recordings of speakers.
DOI: 10.57702/8uvb44zg
title: Neural 3D Mesh Renderer

description: The dataset used in the paper Neural 3D Mesh Renderer. The dataset consists of 3D models of objects.
DOI: 10.57702/3d1yywvb
title: Skoltech Anomaly Benchmark (SKAB)

description: The Skoltech Anomaly Benchmark (SKAB) is a dataset for anomaly detection in time-series data.
DOI: 10.57702/7ehjdbit
title: Head Pose Estimation and 3D Neural Surface Reconstruction

description: The dataset used for head pose estimation and 3D neural surface reconstruction via monocular camera in situ for navigation and safe insertion into natural openings.
DOI: 10.57702/31n9se4b
title: Breast UltraSound Images (BUSI) and private Thyroid UltraSound dataset

description: Breast UltraSound Images (BUSI) and private Thyroid UltraSound dataset used for medical ultrasound segmentation.
DOI: 10.57702/cakkgnhs
title: Urban Sound Propagation

description: The Urban Sound Propagation benchmark is based on the physically complex and practically relevant, yet intuitively easy to grasp task of modeling the 2d propagation of waves from a sound source in an urban environment.
DOI: 10.57702/x3m312yj
title: SSD-Faster Net: A Hybrid Network for Industrial Defect Inspection

description: The dataset used for industrial defect inspection, including metal components, insulators, and commutators.
DOI: 10.57702/imwtvtqv
title: KolektorSDD: A Dataset for Industrial Defect Inspection

description: The dataset used for industrial defect inspection, including metal components, insulators, and commutators.
DOI: 10.57702/pz7wtcib
title: Severstal: A Dataset for Steel Strip Defect Inspection

description: The dataset used for industrial defect inspection, including steel strip defects.
DOI: 10.57702/yxg94irr
title: National Lung Screening Trial

description: Reduced lung-cancer mortality with low-dose computed tomographic screening.
DOI: 10.57702/3e92z8qe
title: Renewable Energy Development and Policies in Singapore, London, and California

description: A dataset containing monthly information on macroeconomic conditions, electricity market structures, and current renewable energy development.
DOI: 10.57702/m63psky5
title: IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization

description: Learning to synthesize data has emerged as a promising direction in zero-shot quantization (ZSQ), which represents neural networks by low-bit integer without accessing any of the real data.
DOI: 10.57702/4ybksdir
title: Real-ESRGAN+

description: Real-ESRGAN+: Real-World Blind Super-Resolution with Sharpened Ground-Truths
DOI: 10.57702/gb9yyxtt
title: Conceptual Captions 3M, Conceptual Captions 12M, RedCaps, and LAION-400M

description: The dataset used in the paper is Conceptual Captions 3M (CC3M), Conceptual Captions 12M (CC12M), RedCaps, and LAION-400M.
DOI: 10.57702/pf4d0kkm
title: Conceptual Captions 12M and RedCaps

description: The dataset used in the paper is Conceptual Captions 12M (CC12M) and RedCaps.
DOI: 10.57702/ol94zi0d
title: COB: Crude Oil Benchmark datasets

description: Real-world time-series benchmark datasets for crude oil prices with distribution shifts
DOI: 10.57702/g21uk3vh
title: Landsat 8 Cloud Cover Assessment Validation Dataset

description: The Landsat 8 Cloud Cover Assessment Validation Dataset was created by Foga et al. from USGS for cloud detection algorithm validation.
DOI: 10.57702/6lxv0qu8
title: Landsat 8 Cloud Cover Assessment (CCA) Validation dataset

description: The Landsat 8 Cloud Cover Assessment (CCA) Validation dataset was created by Foga et al. from USGS for cloud detection algorithm validation.
DOI: 10.5281/zenodo.8360509
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by René Letouzey, http://www.wikidata.org/entity/Q21394446. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21394446
DOI: 10.5281/zenodo.10431556
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Franz Stuhlmann, http://www.wikidata.org/entity/Q107750. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q107750
DOI: 10.5281/zenodo.14183293
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Franz Stuhlmann, http://www.wikidata.org/entity/Q107750. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q107750
DOI: 10.5281/zenodo.14262911
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by René Letouzey, http://www.wikidata.org/entity/Q21394446. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21394446
DOI: 10.5281/zenodo.14262912
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Franz Stuhlmann, http://www.wikidata.org/entity/Q107750. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q107750
DOI: 10.5281/zenodo.8053580
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Franz Stuhlmann, http://www.wikidata.org/entity/Q107750. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q107750
DOI: 10.5281/zenodo.8053581
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Franz Stuhlmann, http://www.wikidata.org/entity/Q107750. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q107750
DOI: 10.5281/zenodo.8360508
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by René Letouzey, http://www.wikidata.org/entity/Q21394446. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21394446
DOI: 10.57702/vlzzrl48
title: OCT2017 dataset

description: Open-access OCT datasets used for pre-training and fine-tuning the model
DOI: 10.57702/8xtfjxmr
title: CHOROID dataset

description: Private OCT dataset used for testing
DOI: 10.5281/zenodo.10823656
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Ernst Bresslau, http://www.wikidata.org/entity/Q1226497. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q1226497
DOI: 10.5281/zenodo.10836095
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Ernst Bresslau, http://www.wikidata.org/entity/Q1226497. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q1226497