cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57702/3weqg4y5
title: ADE20k for semantic segmentation

description: The dataset used in this paper is ADE20k for semantic segmentation.
DOI: 10.57702/ee06noy1
title: DRIVE, STARE, and CHASH_DB1 datasets for medical image segmentation

description: Three medical image segmentation datasets: DRIVE, STARE, and CHASH_DB1.
DOI: 10.57702/02wdqhrx
title: Skin Lesion Analysis Towards Melanoma Detection

description: Skin Lesion Analysis dataset for melanoma detection
DOI: 10.57702/wxk5qrsf
title: Lung Nodule Analysis

description: Lung nodule segmentation dataset.
DOI: 10.57702/otrwvo8x
title: Churn analysis using deep convolutional neural networks and autoencoders

description: Customer temporal behavioral data represented as images to perform churn prediction by leveraging deep learning architectures prominent in image classification.
DOI: 10.57702/q8ln2hj8
title: HSViT: Horizontally Scalable Vision Transformer

description: This paper introduces a horizontally scalable vision transformer (HSViT) scheme with a novel image-level feature embedding. The design of HSViT preserves the inductive bias from convolutional layers while effectively reducing the number of layers and parameters of the models.
DOI: 10.57702/dcs3ahq3
title: Boston Medical Center EHR Dataset

description: The dataset used in this paper is a collection of patients' Electronic Health Records (EHRs) from the Boston Medical Center. The dataset contains information about patients with heart-related diseases and diabetes, including their medical history, recent and more distant hospitalizations, medications, labs, procedures, and clinical observations.
DOI: 10.57702/q4zln9ba
title: KID Dataset

description: Wireless Capsule Endoscopy is one of the most advanced non-invasive methods for the examination of gastrointestinal tracts. An intelligent computer aided diagnostic system for detecting gastrointestinal abnormalities like polyp, bleeding, inﬂammation, etc. is highly exigent in wireless capsule endoscopy image analysis. Abnormalities greatly differ in their shape, size, color, and texture, and some appear to be visually similar to normal regions. This poses a challenge in designing a binary classiﬁer due to intra-class variations.
DOI: 10.57702/fdivtxf2
title: Kvasir-Capsule Dataset

description: Wireless Capsule Endoscopy is one of the most advanced non-invasive methods for the examination of gastrointestinal tracts. An intelligent computer aided diagnostic system for detecting gastrointestinal abnormalities like polyp, bleeding, inﬂammation, etc. is highly exigent in wireless capsule endoscopy image analysis. Abnormalities greatly differ in their shape, size, color, and texture, and some appear to be visually similar to normal regions. This poses a challenge in designing a binary classiﬁer due to intra-class variations.
DOI: 10.57702/6ikjkwyy
title: Learning black- and gray-box chemotactic PDEs/closures from agent-based Monte Carlo simulation data

description: A machine-learning framework for the numerical solution of the inverse problem in chemotaxis.
DOI: 10.57702/u1l01bqq
title: Monte Carlo simulations of E.coli bacterial motility

description: A dataset of high-fidelity, individual-based stochastic simulations of E.coli bacterial motility.
DOI: 10.57702/17zqslz8
title: Deeper, Broader and Artier (DBA) dataset

description: The Deeper, Broader and Artier (DBA) dataset is a large-scale dataset for domain generalization.
DOI: 10.57702/ssohelix
title: Domain Generalization via Jigsaw Puzzle (DGJP) dataset

description: The Domain Generalization via Jigsaw Puzzle (DGJP) dataset is a dataset for domain generalization using jigsaw puzzle.
DOI: 10.57702/8j2wtnrm
title: Deep Domain Generalization (DDG) dataset

description: The Deep Domain Generalization (DDG) dataset is a dataset for domain generalization.
DOI: 10.57702/6dsrrn31
title: Conditional Adversarial Domain Adaptation (CADAN) dataset

description: The Conditional Adversarial Domain Adaptation (CADAN) dataset is a dataset for conditional adversarial domain adaptation.
DOI: 10.57702/lwbg5ljc
title: Domain Adaptation with Geometric Preservation and Distribution Alignment (DAGDA) dataset

description: The Domain Adaptation with Geometric Preservation and Distribution Alignment (DAGDA) dataset is a dataset for domain adaptation with geometric preservation and distribution alignment.
DOI: 10.57702/2zrp62p9
title: MVDiff: Scalable and Flexible Multi-View Diffusion for 3D Object Reconstruction from Single-View

description: Generating consistent multiple views for 3D reconstruction tasks is still a challenge to existing image-to-3D diffusion models.
DOI: 10.57702/q1pkb67r
title: Google Scanned Object (GSO) dataset

description: Google Scanned Object (GSO) dataset contains 3D scanned household items.
DOI: 10.57702/35sbe61s
title: Bengali and Hindi News Articles

description: Bengali dataset consists of articles from online public news portals such as Prothom-Alo, BDNews24 and Nayadiganta. The articles encompass domains such as politics, entertainment, lifestyle, sports, technology and literature. The Hindi dataset consists of Hindinews, Livehindustan and Patrika newspaper articles available open source in Kaggle encompassing similar domains.
DOI: 10.57702/ykztsds6
title: Hindinews and Livehindustan Articles

description: Hindinews, Livehindustan and Patrika newspaper articles available open source in Kaggle encompassing similar domains.
DOI: 10.57702/pwnn0kwa
title: Nayadiganta Dataset

description: Nayadiganta dataset is used as independent test set.
DOI: 10.57702/3vy50qzo
title: Patrika Dataset

description: Patrika dataset is used as independent test set.
DOI: 10.57702/euk6zy1e
title: Visual Wake Words (VWW) dataset

description: The Visual Wake Words (VWW) dataset consists of high-resolution images that include visual cues to 'wake-up' AI-powered home assistant devices.
DOI: 10.57702/hfs95qh9
title: Quora

description: The Quora dataset is a large-scale dataset for information-seeking conversation systems. It contains questions and answers, and is used to evaluate the performance of information-seeking conversation systems.
DOI: 10.57702/a350j4lb
title: MuST-C: a Multilingual Speech Translation Corpus

description: MuST-C is a multilingual speech translation corpus.
DOI: 10.57702/64fhtod7
title: LEVIR-CD and SYSU-CD datasets

description: LEVIR-CD and SYSU-CD datasets for remote sensing change detection and urban prediction tasks
DOI: 10.57702/nvq31ald
title: Social Chemistry 101

description: Social Chemistry 101 dataset is a collection of social norms and rules of thumb (ROTs) for evaluating people's behavior in everyday social situations.
DOI: 10.57702/14yb226n
title: Symbolic Pregression: Discovering Physical Laws from Distorted Video

description: A method for unsupervised learning of equations of motion for objects in raw and optionally distorted unlabeled video.
DOI: 10.57702/8wanl22y
title: Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesis

description: Cross-modality medical image synthesis is a critical topic and has the potential to facilitate numerous applications in the medical imaging field.
DOI: 10.57702/xjalcsbi
title: MovieLens 20M Dataset

description: The dataset used in this paper is a high-rating movie recommendation system. The objective of the system is to recommend high-rating movies to users, but the ratings for the considered movies are unknown in advance. Thus, the system needs to learn the ratings of the movies while simultaneously recommending the high-rating ones to its users.
DOI: 10.57702/vyr3fblh
title: VeRi

description: The VeRi dataset is a large-scale vehicle re-identification dataset, containing over 50,000 images of 776 vehicles.
DOI: 10.57702/cpmd2d7g
title: ATCN: Agile Temporal Convolutional Network

description: This paper presents a scalable deep learning model called Agile Temporal Convolutional Network (ATCN) for high-accurate fast classiﬁcation and time series prediction in resource-constrained embedded systems.
DOI: 10.57702/9l7el6vr
title: UCR Time Series Archive

description: UCR Time Series Archive is a collection of time series datasets from various domains. It is used for training and testing deep neural networks for time series classification tasks.
DOI: 10.57702/gojkzur1
title: DENTEX

description: The dataset is used for panoramic dental X-ray analysis, specifically for abnormal tooth detection with quadrant, enumeration, and diagnosis.
DOI: 10.57702/phbjsspf
title: ISBI 2017 Dataset

description: The dataset used for lymphoma classification, IDC detection, nuclei segmentation, epithelium segmentation, tubule segmentation, lymphocyte detection, and mitosis detection.
DOI: 10.57702/inhp84e8
title: ISBI 2014 Dataset

description: The dataset used for invasive ductal carcinoma detection in whole slide images.
DOI: 10.57702/39oaqdj5
title: Tubule Segmentation Dataset

description: The dataset used for tubule segmentation of inhomogeneity images based on convolutional neural networks with fluorescence microscopy correction.
DOI: 10.57702/xn8ui949
title: Breast Cancer Segmentation Dataset

description: The dataset used for automatic glandular and tubule region segmentation in histological grading of breast cancer.
DOI: 10.57702/z6ols4uf
title: Mitosis Detection Dataset

description: The dataset used for mitosis detection in breast cancer histology images with deep neural networks.
DOI: 10.57702/3302m9ze
title: UTE dataset

description: The dataset is used for traffic tasks, focusing on vehicle trajectory data.
DOI: 10.57702/bolxnw0d
title: Slake

description: Slake is a medical visual question answering dataset.
DOI: 10.57702/rmflqcl5
title: UniDual: A Uniﬁed Model for Image and Video

description: The UniDual model jointly learns from both images and videos.
DOI: 10.57702/8dl5n13n
title: Sports1M

description: The Sports1M dataset contains 1 million sports videos, with 500K training videos and 500K validation videos.
DOI: 10.57702/vrbsu47s
title: CartPole-v1, LunarLander-v2, Maze Traversal

description: CartPole-v1, LunarLander-v2, Maze Traversal
DOI: 10.57702/ommgynnb
title: GIMO

description: The GIMO dataset contains motion and gaze data captured from 11 participants.
DOI: 10.57702/x3rgs0ha
title: Tanks and Temples Advanced (T&T) Dataset

description: The Tanks and Temples Advanced (T&T) dataset is a benchmark dataset for image-based 3D reconstruction. It contains 90% images for training and 10% images for evaluation.
DOI: 10.57702/a6fr4isg
title: Mutant and LEGO Dataset

description: The Mutant and LEGO dataset is a dynamic scene dataset. It contains 90% images for training and 10% images for evaluation.
DOI: 10.57702/b5jlsdyr
title: Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

description: Training text-to-image models with web scale image-text pairs enables the generation of a wide range of visual concepts from text. However, these pre-trained models often face challenges when it comes to generating highly aesthetic images. This creates the need for aesthetic alignment post pre-training. In this paper, we propose quality-tuning to effectively guide a pre-trained model to exclusively generate highly visually appealing images, while maintaining generality across visual concepts.
DOI: 10.57702/zmsvfjx4
title: Text-to-image generation via masked generative transformers

description: Text-to-image generation via masked generative transformers.
DOI: 10.57702/xipdnib9
title: Learning to follow image editing instructions

description: Learning to follow image editing instructions.
DOI: 10.57702/zkdhymok
title: Adding conditional control to text-to-image diffusion models

description: Adding conditional control to text-to-image diffusion models.
DOI: 10.57702/2s24x3tj
title: NGA-West2

description: The NGA-West2 database contains approximately 16000 peak ground acceleration (PGA) and velocity (PGV) from the NGA-West2 database are used to discover the GMM and develop the GMPE.
DOI: 10.57702/32s1m5ik
title: Douban Online-ofﬂine

description: The dataset used in the paper for anchor link prediction, constructed by combining source and target networks.
DOI: 10.57702/qdotrp2b
title: one-million-reddit-questions

description: The dataset contains 500 questions from one million open-ended requests posted on AskReddit, and 129,483 of these questions were identified as asking for help.
DOI: 10.57702/s24j8isg
title: DeFTAN-II: Efficient Multichannel Speech Enhancement with Subgroup Processing

description: Multichannel speech enhancement model based on transformer architecture and subgroup processing
DOI: 10.57702/1opw1b8o
title: Complex spectral mapping for single-and multi-channel speech enhancement and robust ASR

description: Multichannel speech enhancement model using complex spectral mapping and masking
DOI: 10.57702/z4uri0ho
title: TPARN: Triple-path attentive recurrent network for time-domain multichannel speech enhancement

description: Multichannel speech enhancement model using triple-path attentive recurrent network
DOI: 10.57702/alusfyp5
title: REAL

description: The REAL dataset is a real-world dataset capturing 4300 real-world images of 7 scenes for training, and 2750 real-world images of 6 scenes for evaluation.
DOI: 10.57702/60sz6vhu
title: DOLaH

description: A dataset containing 2,026 Facebook posts collected from Twitter, labeled as offensive or non-offensive.
DOI: 10.57702/tj4q8xha
title: Hybrid Quantum-Classical Neural Network with Deep Residual Learning

description: A hybrid quantum-classical neural network with deep residual learning to improve the performance of cost function for deeper networks.
DOI: 10.57702/j9u4n3ur
title: Development and characterization of a chest CT atlas

description: Development and characterization of a chest CT atlas.
DOI: 10.57702/peuakzvz
title: THuman2.0

description: A dataset for 3D human digitization from a single image. The approach synthesizes a 360-degree view of a person with a consistent, high-resolution appearance from a single input image.
DOI: 10.57702/wrdyr2t8
title: Tex2Shape

description: The Tex2Shape dataset contains 3D human models with various poses and clothing.
DOI: 10.57702/m9smyxsx
title: PIFu

description: The PIFu dataset contains 3D human models with various poses and clothing.
DOI: 10.15468/dl.nkt8k9
title: Occurrence Download

description: A dataset containing 173699 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Material sample)",
 "Country is United States of America",
 "Geometry POLYGON((-96.40538 22.81461,-63.91051 22.81461,-63.91051 44.22299,-96.40538 44.22299,-96.40538 22.81461))",
 "OccurrenceStatus is Present",
 "TaxonKey is Cnidaria"
 ]
}

 The dataset includes 173699 records from 112 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013504-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/3u5v1wf5
title: Container: A General-Purpose Building Block for Multi-Head Context Aggregation

description: Convolutional neural networks (CNNs) are ubiquitous in computer vision, with a myriad of effective and efﬁcient variations. Recently, Transformers – originally introduced in natural language processing – have been increasingly adopted in computer vision.
DOI: 10.57702/n0g1w01t
title: ELIGN: Expectation Alignment as a Multi-Agent Intrinsic Reward

description: Modern multi-agent reinforcement learning frameworks rely on centralized training and reward shaping to perform well. However, centralized training and dense rewards are not readily available in the real world. Current multi-agent algorithms struggle to learn in the alternative setup of decentralized training or sparse rewards.
DOI: 10.57702/3fdfl6lg
title: Multi-Agent Particle Environment and Google Research Football Environment

description: Multi-agent particle environment and Google Research football environment.
DOI: 10.57702/tlyf97u8
title: SMMNIST

description: The SMMNIST dataset is an extension of the MNIST dataset, where the digit images form a temporal sequence, creating dynamic scenes as a result of random movements of the black-and-white digits.
DOI: 10.57702/t3dwxct5
title: UVG

description: The UVG dataset comprises 16 video sequences of 3840×2160, recorded at 120 frames per second.
DOI: 10.57702/z9chl0jz
title: ScanNetV2

description: The dataset used in the paper is ScanNetV2, a real-world dataset for indoor scenes. It contains 1205 training scenes and 312 testing scenes, with instance-level object bounding box labels provided for 18 categories.
DOI: 10.57702/ig9jbhbp
title: TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videos

description: Weakly supervised video object localization (WSVOL) allows locating object in videos using only global video tags such as object classes.
DOI: 10.57702/dwp4rfr6
title: YouTube-Objects v1.0 and v2.2

description: YouTube-Objects v1.0 and v2.2 datasets are used for evaluation.
DOI: 10.57702/o9raffed
title: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

description: Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes during training, as the parameters of the previous layers change.
DOI: 10.57702/enx7yqwa
title: Deep Image: Scaling up image recognition

description: Deep Image: Scaling up image recognition
DOI: 10.57702/7f68zqd1
title: THE MIRRORNET: LEARNING AUDIO SYNTHESIZER CONTROLS INSPIRED BY SENSORIMOTOR INTERACTION

description: The MirrorNet model is applied to learn, in an unsupervised manner, the controls of a specific audio synthesizer (DIVA) to produce melodies only from their auditory spectrograms.
DOI: 10.57702/4jbu7o45
title: 3DTopia-360K

description: The 3DTopia-360K dataset is a large-scale 3D object dataset, which is used to train the 3DTopia model. The dataset contains 360K 3D objects with detailed captions.
DOI: 10.57702/t3389izm
title: MUAD: Multiple Uncertainties for Autonomous Driving

description: MUAD: A synthetic dataset for autonomous driving with multiple uncertainties and annotations for semantic segmentation, depth estimation, object detection, and instance segmentation.
DOI: 10.5281/zenodo.11372850
title: AN EXTENSION OF N-MIXTURE OCCUPANCY MODELS FOR COUNT DATA
DOI: 10.57702/ijoqzew3
title: Fishyscapes

description: Fishyscapes: A benchmark for safe semantic segmentation in autonomous driving with annotations for pedestrian and vehicle detection.
DOI: 10.5281/zenodo.11372849
title: AN EXTENSION OF N-MIXTURE OCCUPANCY MODELS FOR COUNT DATA
DOI: 10.5281/zenodo.14263007
title: AN EXTENSION OF N-MIXTURE OCCUPANCY MODELS FOR COUNT DATA
DOI: 10.57702/oc7yzo24
title: CIFAR-10 and STL-10 datasets

description: The CIFAR-10 dataset is a collection of 60,000 32x32 color images in 10 classes, and the STL-10 dataset is a collection of 90,000 96x96 color images in 10 classes.
DOI: 10.57702/r7d18nov
title: Amazon@Beauty and Amazon@Books datasets

description: The Amazon@Beauty dataset is a collection of product reviews from Amazon.com, and the Amazon@Books dataset is a collection of product reviews from Amazon.com.
DOI: 10.57702/yxh7241i
title: Multi-objective Differentiable Neural Architecture Search

description: The authors propose a novel hardware-aware differentiable NAS algorithm for profiling the Pareto front in multi-objective problems.
DOI: 10.57702/mx2bhxe2
title: Monas: Multi-objective neural architecture search using reinforcement learning

description: The authors propose a multi-objective neural architecture search using reinforcement learning.
DOI: 10.57702/nf9qmeqe
title: ProxylessNAS: Direct neural architecture search on target task and hardware

description: The authors propose a proxyless NAS algorithm that can be used for efficient deployment.
DOI: 10.57702/nk86v7ml
title: ManifoldNeRF: Few-shot Novel View Synthesis

description: ManifoldNeRF is a few-shot novel view synthesis method that uses a manifold loss function to provide supervision for arbitrary viewpoints.
DOI: 10.57702/yz7tqhan
title: DTU MVS Dataset

description: The DTU MVS dataset contains 49 images of physical objects in real environments.
DOI: 10.57702/u9zxari6
title: NLCD

description: National Land Cover Database (NLCD) dataset
DOI: 10.15468/dl.x9wpq5
title: Occurrence Download

description: A dataset containing 465 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Metlapilcoatlus mexicanus (Duméril, Bibron & Duméril, 1854)"
 ]
}

 The dataset includes 465 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013596-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/aeelnqr9
title: ImageNet-32

description: The ImageNet-32 dataset is a subset of the ImageNet dataset, containing 1,281,167 training samples and 50,000 test samples, distributed across 1,000 labels.
DOI: 10.57702/fbq7pfbh
title: Point Cloud Shape Completion Dataset

description: The dataset used in the paper is a dataset for training and testing the proposed RL-GAN-Net model.
DOI: 10.57702/544l1y58
title: CLIC professional-train dataset

description: The dataset used in the paper is the CLIC professional-train dataset, which contains images that are too large to fit into the eight gigabytes memory of Nvidia Geforce GTX1070.
DOI: 10.15468/dl.7eun4j
title: Occurrence Download

description: A dataset containing 209 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atelocynus microtis (Sclater, 1883)"
 ]
}

 The dataset includes 209 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013591-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uycuzx
title: Occurrence Download

description: A dataset containing 8035 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ateles geoffroyi Kuhl, 1820"
 ]
}

 The dataset includes 8035 records from 103 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013595-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/rqvxw29p
title: ImageNet, CIFAR-10, and Cityscapes

description: The dataset used in this paper is ImageNet and CIFAR-10 for image classification, and Cityscapes for semantic segmentation.
DOI: 10.15468/dl.x8sqjr
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Ambystoma mexicanum (Shaw & Nodder, 1798)",
 "Year 2000-2024"
 ]
}

 The dataset includes 17 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013599-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/y61dmfk6
title: BEHAVE

description: The BEHAVE dataset is annotated with text descriptions for 3D human-object interactions.
DOI: 10.15468/dl.ujp96s
title: Occurrence Download

description: A dataset containing 20622 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eichhornia crassipes (Mart.) Solms"
 ]
}

 The dataset includes 20622 records from 610 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013590-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.