cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.23641/asha.27616845
title: Device delay mismatch and speech recognition (Richter et al., 2024)

description: <b>Purpose: </b>Cochlear implant (CI) recipients who listen with a hearing aid (HA) in the contralateral ear, known as bimodal listeners, demonstrate individual variability in speech recognition in noise. This variability may be due in part to differences in the processing delays of the CI and HA devices. This study investigated the influence of matching the processing delays of CI and HA devices on masked speech recognition for bimodal listeners.<b>Method: </b>Twelve postlingually deafened adult CI recipients completed a task of masked speech recognition in two listening conditions: (a) independent default CI and HA processing delays (mismatched) and (b) with their HA-specific delay applied to the CI processing delay (matched). Speech recognition was evaluated with AzBio sentences presented in a 10-talker masker at a 0 dB SNR. The target was presented from the front loudspeaker at 0° azimuth, and the masker was co-located with the target, presented 90° toward the CI ear, or presented 90° toward the HA ear.<b>Results: </b>There was a significant main effect for target-to-masker configuration, with better performance when the masker was spatially separated from the target. Better masked speech recognition was observed in the matched condition as compared to the mismatched condition.<b>Conclusion: </b>Bimodal listeners may experience better masked speech recognition when the processing delay of the CI is individualized to match the processing delay of the contralateral HA.<b>Supplemental Material S1.</b> Raw data of speech recognition across masker configurations for the sample, ranked by age at time of test. Listed in percent correct for each condition.Richter, M. E., Rooth, M. A., & Dillon, M. T. (2024). Influence of matching the processing delays of cochlear implant and hearing aid devices for bimodal listeners on speech recognition in noise. <i>American Journal of Audiology, 33</i>(4), 1350–1355. https://doi.org/10.1044/2024_AJA-24-00026
DOI: 10.57702/4l0vu6r9
title: LiDAR-based 3D Object Detection Dataset

description: LiDAR-based 3D object detection dataset
DOI: 10.57702/hopz5b32
title: RFDiffusion motif benchmark

description: The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a discrete-time DDPM formulation for the diffusion model with N = 1000 steps and cosine β-schedule.
DOI: 10.57702/agcqtup3
title: Asian Option Pricing via Laguerre Quadrature: A Diffusion Kernel Approach

description: The dataset used in this paper is the Asian Option Pricing via Laguerre Quadrature: A Diffusion Kernel Approach.
DOI: 10.57702/s1m88dug
title: Fred-MD: A monthly database for macroeconomic research

description: A monthly database for macroeconomic research
DOI: 10.57702/fmueeaf1
title: HDR Video Reconstruction with a Large Dynamic Dataset in Raw and sRGB Domains

description: A large-scale real-world LDR-HDR video dataset with 85 scenes and each scene contains 60 frames. The dataset is constructed by capturing two alternate exposure images simultaneously using a staggered sensor.
DOI: 10.57702/1bkdvtkq
title: Portrait Diffusion: Training-free Face Stylization with Chain-of-Painting

description: Face stylization refers to the transformation of a face into a specific portrait style. However, current methods require the use of example-based adaptation approaches to fine-tune pre-trained generative models.
DOI: 10.57702/0elnaxd7
title: ImageNet: A Large-Scale Hierarchical Image Database

description: The ImageNet dataset is a large-scale image database that contains over 14 million images, each labeled with one of 21,841 categories.
DOI: 10.57702/51b7f1mf
title: Vi-Fi Multi-modal Dataset

description: The dataset used in the paper for layout sequence prediction from noisy mobile modality.
DOI: 10.57702/ua0nc955
title: H3D Dataset

description: The H3D dataset for full-surround 3D multi-object detection and tracking in crowded urban scenes.
DOI: 10.57702/syhh7vq2
title: Zhixue1 dataset

description: The dataset is a large-scale real-world dataset collected from Zhixue1, a widely-used online learning system, which provided high school students with a large number of exercise resources for exercising.
DOI: 10.57702/r05yy1ry
title: ExPI

description: A dataset for human motion synthesis, consisting of 3D human motion data and corresponding text descriptions.
DOI: 10.57702/o5onnkq2
title: UMPM

description: A dataset for human motion synthesis, consisting of 3D human motion data and corresponding text descriptions.
DOI: 10.57702/rcnjjpty
title: GraphBGS: Background Subtraction via Recovery of Graph Signals

description: Background subtraction is a fundamental pre-processing task in computer vision. This task becomes challenging in real scenarios due to variations in the background for both static and moving camera sequences.
DOI: 10.57702/qheekvvi
title: CDNet2014

description: Change Detection (CDNet2014) is a benchmark dataset for change detection in videos.
DOI: 10.57702/lqxtaaqm
title: UCSD Background Subtraction Dataset

description: UCSD background subtraction dataset contains videos with moving camera sequences.
DOI: 10.57702/ex2bpn8k
title: Dirlab-COPDGene dataset

description: The Dirlab-COPDGene dataset is a collection of lung CT scans with annotated landmark correspondences.
DOI: 10.57702/qofhfpvg
title: AVSS 2018 challenge II

description: The AVSS 2018 challenge II dataset is used for semantic person retrieval using soft biometrics. It contains two tasks: person re-identification and surveillance imagery search.
DOI: 10.57702/ahvcq5gb
title: RAP dataset

description: The RAP dataset is used for pedestrian attribute recognition. It contains large-scale pedestrian attribute datasets.
DOI: 10.57702/u3zyaz7f
title: Synthetic Neural Data

description: The dataset used in this paper is a synthetic neural data generated using the Arneodo system.
DOI: 10.57702/9uraqgf9
title: TB-Places data set

description: Extended version of the TB-Places data set, containing images recorded in real gardens in different seasons, with varying light conditions.
DOI: 10.57702/txvnma61
title: Few-shot semantic segmentation via prototype augmentation with image-level annotations

description: Few-shot semantic segmentation via prototype augmentation with image-level annotations
DOI: 10.57702/6k0o15qm
title: MS COCO dataset

description: The MS COCO dataset is a large benchmark for image captioning, containing 328K images with 5 caption descriptions each.
DOI: 10.57702/xp3x2tef
title: BENCHMARK ASSESSMENT FOR DEEPSPEED OPTIMIZATION LIBRARY

description: Deep Learning (DL) models are widely used in machine learning due to their performance and ability to deal with large datasets while producing high accuracy and performance metrics.
DOI: 10.57702/u2rif45m
title: DVS128 Gesture, CIFAR10-DVS, N-Caltech101

description: The dataset used in the paper is a neuromorphic dataset, specifically the DVS128 Gesture dataset, CIFAR10-DVS dataset, and N-Caltech101 dataset.
DOI: 10.57702/8uwl35ui
title: MNIST dataset for bandit problem

description: The MNIST dataset is a well-known image dataset for the 10-class classification problem. Following the evaluation setting of existing works, we transform this classification problem into a bandit problem.
DOI: 10.57702/d7sil3ez
title: MovieLens dataset

description: The MovieLens dataset contains questions answerable using Wikidata as the knowledge graph, focusing on questions with a single entity and relation.
DOI: 10.57702/tewkepok
title: Disin dataset

description: The Disin dataset is a fake news dataset on Kaggle, including 12,600 fake news articles and 12,600 truthful news articles.
DOI: 10.57702/6f9palsp
title: FlipNeRF

description: The FlipNeRF dataset is used for few-shot novel view synthesis.
DOI: 10.57702/q65oq6yh
title: Sparsenerf

description: The Sparsenerf dataset is used for few-shot novel view synthesis.
DOI: 10.57702/hustgho6
title: BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

description: Semantic segmentation requires both rich spatial information and sizeable receptive field. However, modern approaches usually compromise spatial resolution to achieve real-time inference speed, which leads to poor performance.
DOI: 10.57702/z9l3b9nl
title: Pyramid scene parsing network

description: Pyramid scene parsing network for semantic segmentation.
DOI: 10.57702/qrbpjj8a
title: IXI dataset

description: The dataset consists of T1-weighted brain MRI images of patients, with manual segmentation of anatomical structures provided.
DOI: 10.57702/nim59ts8
title: Inductive Matrix Completion Using Graph Autoencoder

description: Matrix completion has been formulated as the link prediction problem on a bipartite user-item graph in recent GNN-based matrix completion methods.
DOI: 10.57702/gijd0y59
title: MovieLens-100K and MovieLens-1M

description: MovieLens-100K and MovieLens-1M datasets are used for performance testing of comparative experiments.
DOI: 10.57702/zeq2gqqg
title: Yahoo! Music

description: The Yahoo! Music dataset is a collection of user-item interactions.
DOI: 10.57702/ebxafjtq
title: BACH 2018 grand challenge

description: Breast cancer histology images classification using transfer learning
DOI: 10.57702/tn1yvq8p
title: Green Supply Chain Model

description: A green supply chain model has been developed by various authors, including Sheu et al. (2005), Ding et al. (2005), Pan and Wu (2014).
DOI: 10.57702/u6907zdn
title: Fine-Grained Head Pose Estimation Without Keypoints

description: Estimating the head pose of a person is a crucial problem that has a large amount of applications such as aiding in gaze estimation, modeling attention, fitting 3D models to video and performing face alignment.
DOI: 10.57702/tsximo4e
title: 3DDFA
DOI: 10.57702/6oxvjni6
title: FAN
DOI: 10.57702/n0xd2fkx
title: AFLW

description: Facial landmark detection aims to detect the location of predeﬁned facial landmarks, such as the corners of the eyes, eyebrows, the tip of the nose. It has drawn much attention recently as it is a prerequisite in many computer vision applications.
DOI: 10.57702/8tkcgcp8
title: Zero-NeRF: Registration with Zero Overlap

description: A dataset for registration of real-world scenes from opposite sides with inﬁnitesimal overlaps that cannot be accurately registered using prior methods.
DOI: 10.57702/azw1stge
title: Grapevine Dataset

description: A dataset for registration of real-world grapevine scans and a synthetic dataset with known ground truth registration.
DOI: 10.57702/km4sry5s
title: Datacomp

description: The dataset used in the paper for training and evaluation of the HYPE method.
DOI: 10.57702/lu87nf50
title: ECUST Food Dataset (ECUSTFD)

description: A novel food image dataset with volume and mass records of foods, and a deep learning method for food detection, to make a complete calorie estimation.
DOI: 10.57702/2a5w5m90
title: Pittsburgh Fast-food Image Dataset (PFID)

description: A food image dataset including still images and videos of fast foods.
DOI: 10.57702/qi4w9ziq
title: Extracting Stochastic Governing Laws by Nonlocal Kramers-Moyal Formulas

description: The dataset used in this paper is a short bursts of simulation data from stochastic diﬀerential equations with non-Gaussian Lévy noise.
DOI: 10.57702/aa77ik7h
title: EDDense-Net: Fully Dense Encoder Decoder Network for Joint Segmentation of Optic Cup and Disc

description: The proposed EDDense-Net segmentation network for the joint segmentation of optic cup and disc in retinal fundus images.
DOI: 10.57702/pje70z24
title: DRISHTI-GS

description: A comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis.
DOI: 10.57702/4qa3ryfm
title: RIM-ONE

description: An open retinal image database for optic nerve evaluation.
DOI: 10.57702/49hm8r40
title: Deep Learning-Aided Tabu Search Detection for Large MIMO Systems

description: The proposed FS-Net detection scheme is a DNN-aided symbol-detection algorithm for MIMO systems. Unlike the prior DetNet and ScNet schemes, the input vector of the FS-Net is optimized such that a reduced number of connections is required in each layer. Furthermore, the correlation between the input and output signals is considered in the loss function of the FS-Net, allowing it to be trained better with faster convergence compared to DetNet and ScNet.
DOI: 10.57702/rvj3rp8y
title: Cardiac Resynchronisation Therapy

description: A dataset of cardiac magnetic resonance images used for predicting response to cardiac resynchronization therapy.
DOI: 10.57702/g5uyy0qu
title: MNIST, Fashion-MNIST, and Kuzushiji-MNIST

description: Three public datasets were employed throughout the experiments: MNIST, Fashion-MNIST, and Kuzushiji-MNIST.
DOI: 10.57702/k9p95tx9
title: In-vitro dataset

description: The dataset used for training and testing the proposed Tiny-VBF model, which is a vision transformer-based image reconstruction for ultrasound imaging.
DOI: 10.57702/fpagvnx1
title: In-silico dataset

description: The dataset used for testing the proposed Tiny-VBF model, which is a vision transformer-based image reconstruction for ultrasound imaging.
DOI: 10.57702/ziirue5j
title: Brazil Wind and Solar Power Generation Data

description: The dataset used in this paper is a real-world wind and solar power generation data from the Brazil system.
DOI: 10.57702/gqc126zu
title: Lip Reading in the Wild (LRW)

description: Lip reading aims to recognize speech content from videos via visual analysis of speakers' lip movements. This is a challenging task due to the existence of homophemes – words which involve identical or highly similar lip movements, as well as diverse lip appearances and motion patterns among the speakers.
DOI: 10.57702/eqs71nxo
title: LRW-1000

description: LRW-1000 is a challenging Mandarin lip-reading dataset due to its large variations in scale, resolution, background clutter, and speaker attributes.
DOI: 10.57702/l9uh1xaz
title: MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers

description: MaX-DeepLab: End-to-end panoptic segmentation with mask transformers
DOI: 10.57702/sjkug8pe
title: Curated Breast Imaging Subset of Digital Database of Screening Mammography (CBIS-DDSM)

description: The Curated Breast Imaging Subset of Digital Database of Screening Mammography (CBIS-DDSM) dataset is used for both training and testing of the developed deep learning approach.
DOI: 10.57702/lgbryz3z
title: SGVAE: Sequential Graph Variational Autoencoder

description: Generative models of graphs are well-known, but many existing models are limited in scalability and expressivity. We present a novel sequential graphical variational autoencoder operating directly on graphical representations of data.
DOI: 10.57702/5296rzmg
title: BraTS2018

description: The BraTS2018 database is a continually evolving database with a total of 285 glioblastoma or low-grade gliomas subjects, comprising three consecutive subsets, i.e., 30 subjects from BraTS2013, 167 subjects from TCIA, and 88 subjects from CBICA.
DOI: 10.57702/9oevh8zk
title: TCIA

description: The dataset used in the paper is a collection of medical images of patients diagnosed with glioblastoma multiforme, which is a type of brain cancer.
DOI: 10.57702/0fvbrnn4
title: Extended SVHN

description: The dataset used for training and testing Binarized Convolutional Neural Network architectures (LeNet-4, Network-In-Network, AlexNet) on various datasets.
DOI: 10.57702/48c8gqv6
title: GeoConv: Geodesic Guided Convolution for Facial Action Unit Recognition

description: Automatic facial action unit (AU) recognition has attracted great attention but still remains a challenging task, as subtle changes of local facial muscles are difficult to thoroughly capture. Most existing AU recognition approaches leverage geometry information in a straightfor-ward 2D or 3D manner, which either ignore 3D manifold information or suffer from high computational costs.
DOI: 10.57702/5b7ue75h
title: DynamicRadCineMRI

description: The dataset used in this paper for dynamic multi-coil MR image reconstruction using non-uniformly sampled data.
DOI: 10.57702/0w9ulbvd
title: PASCAL VOC, COCO, TJU-DHD, and ImageNet datasets

description: The dataset used in the paper for object detection, featuring images from PASCAL VOC, COCO, TJU-DHD, and ImageNet.
DOI: 10.57702/cr0wblrk
title: MultiCorpus

description: The MultiCorpus dataset is a diverse and acoustically adverse dataset generated by mixing reverberant speech and reverberant noise using speech utterances, noise segments and binaural room impulse responses (BRIRs).
DOI: 10.57702/dlbe7iv4
title: US America Temperature dataset

description: The dataset contains hourly temperature data for major cities in the United States.
DOI: 10.57702/1azkwvit
title: Arcade Learning Environment (ALE) dataset

description: The dataset used in the paper is the Arcade Learning Environment (ALE) dataset, which consists of 57 classic Atari games.
DOI: 10.57702/ljwpq1bq
title: BraTS2021 dataset

description: The BraTS2021 dataset is an important resource in the field of brain tumor segmentation, consisting of multi-modal magnetic resonance imaging (MRI) data, including four imaging modalities: T1, T1ce, T2, and FLAIR. The imaging data for each patient has a resolution of 240×240×155, with a voxel size of 1×1×1 mm³.
DOI: 10.57702/ngmipp9w
title: ImageNet and CC12M datasets

description: The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the ImageNet dataset and a subset of the CC12M dataset for training.
DOI: 10.57702/y2gme96b
title: LAION-5B dataset

description: The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the LAION-5B dataset for training.
DOI: 10.57702/2rhv8oi0
title: Modular U-Net for automated segmentation of X-ray tomography images in composite materials

description: A reinterpretation of the U-Net architecture as a modularized structure was proposed as a solution to scale up the segmentation of such images.
DOI: 10.57702/8t5d6vj4
title: Gridworld Dataset

description: The dataset used for the Gridworld tasks, consisting of 10K episodes of the agent following a uniform random policy.
DOI: 10.57702/hw3w7u3o
title: Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation

description: A high-quality variable-length multi-frame interpolation method for video interpolation
DOI: 10.57702/zod0h8e9
title: Adobe 240-fps

description: A dataset for video deblurring
DOI: 10.57702/xd4tqhoz
title: OfficeHome

description: OfficeHome dataset comprises four different domains, including Clipart and Real World, and is used to validate generalization ability across domains in few-shot settings.
DOI: 10.57702/fggeb0iw
title: Automated age-related macular degeneration area estimation – ﬁrst results

description: The dataset is used for automatic method for detecting Age-related Macular Degeneration (AMD) lesions in RGB eye fundus images.
DOI: 10.57702/spy0ylws
title: Ornstein-Uhlenbeck process

description: The dataset used in the paper is an Ornstein-Uhlenbeck process, which is a type of diffusion process.
DOI: 10.57702/bxxjgaxy
title: iSeg-2017

description: Medical image segmentation dataset for infant brain images
DOI: 10.57702/01p16ddz
title: Cardiac

description: Cardiac dataset contains cardiac MRI scans with 3 annotated structures.
DOI: 10.57702/z3kvlh3k
title: Seattle's GPS Trajectory Dataset

description: The dataset used in this paper is a GPS trajectory dataset collected from a vehicle in Seattle, with 7351 GPS records, including latitude and longitude with a time stamp.
DOI: 10.57702/1kmttwwb
title: Seattle's Digital Road Network

description: The dataset used in this paper is a digital road network dataset, consisting of more than 8500 roads, used for map-matching.
DOI: 10.57702/wknt225n
title: CARLA simulator datasets for pedestrian detection

description: Three datasets: training, calibration, and evaluation datasets for pedestrian detection task.
DOI: 10.57702/jl2w2uvw
title: LoDoPaB-CT dataset

description: The LoDoPaB-CT dataset is used to test the reconstruction methods. The dataset consists of 284,672 training samples and 10,000 test samples.
DOI: 10.57702/8pggrljx
title: Moving Mnist++

description: A dataset used for evaluating the performance of cloudage nowcasting models.
DOI: 10.57702/btet7ybb
title: IMDB dataset

description: The IMDB dataset is a polarity dataset for sentiment analysis or text classification, it contains 50000 sentences and their binary class labels, being either "Positive" or "Negative".
DOI: 10.57702/bjjk7qel
title: SpoC: Spooﬁng Camera Fingerprints

description: A GAN-based method to attack both forensic camera model identiﬁers and GAN detectors.
DOI: 10.57702/lnn731tj
title: Camera Model Identiﬁcation Challenge

description: A dataset for camera model identiﬁcation using convolutional neural networks.
DOI: 10.57702/x4st0xsc
title: Temporally-Adaptive Convolutions for Video Understanding

description: Spatial convolutions are extensively used in numerous deep video models. It fundamentally assumes spatio-temporal invariance, i.e., using shared weights for every location in different frames. This work presents Temporally-Adaptive Convolutions (TAdaConv) for video understanding, which shows that adaptive weight calibration along the temporal dimension is an efficient way to facilitate modeling complex temporal dynamics in videos.
DOI: 10.57702/582dky7a
title: Epic-Kitchens-100

description: The Epic-Kitchens-100 dataset contains 97 verb and 300 noun classes with actions defined by the combination of nouns and verbs.
DOI: 10.57702/3arwp6wq
title: HACS

description: The HACS dataset contains 200 action classes with 504K videos.
DOI: 10.57702/i1ddyaxm
title: SmokeSeg

description: SmokeSeg dataset for early smoke segmentation, containing 6144 real images with pixel-wise annotations.
DOI: 10.57702/95nf5tb4
title: SMOKE5K

description: SMOKE5K dataset for smoke segmentation, containing 400 real images.
DOI: 10.57702/f9dtu19q
title: SYN70K

description: SYN70K dataset for smoke segmentation, containing 70k synthetic images.
DOI: 10.57702/jrgkyfne
title: SEMI-SUPERVISED COMPLEX-VALUED GAN FOR POLARIMETRIC SAR IMAGE CLASSIFICATION

description: Polarimetric synthetic aperture radar (PolSAR) images are widely used in disaster detection and military reconnaissance and so on. However, their interpretation faces some challenges, e.g., deficiency of labeled data, inadequate utilization of data information and so on.
DOI: 10.57702/ra62lcjs
title: UCI regression tasks and UTKFace dataset

description: The dataset used in the paper is a collection of UCI regression tasks and a network pretrained for face age estimation.
DOI: 10.57702/5fdf24wa
title: BanglaLekhaImageCaptions dataset

description: The BanglaLekhaImageCaptions dataset is a modified version of the dataset introduced in [24]. It contains 9,154 images with two captions for each image.
DOI: 10.57702/qwvgc2cb
title: NIH chest radiography dataset

description: Replicated the model described in Rajpurkar et al. with fixed hyperparameters and 50 different random seeds to identify 14 findings in chest radiographs.
DOI: 10.57702/mmzm1ko2
title: CheXpert dataset

description: Chest radiography is a relatively cheap, widely available medical procedure that conveys key information for making diagnostic decisions. Chest X-rays are frequently used in the diagnosis of respiratory diseases such as pneumonia or COVID-19.
DOI: 10.57702/natrwhtb
title: MIMIC-CXR dataset

description: The MIMIC-CXR dataset is currently the largest radiology imaging dataset available. It comprises a total of 473,057 chest X-ray images and 206,563 associated radiology diagnostic reports.
DOI: 10.57702/4dg7bqj0
title: Tienet dataset

description: A text-image embedding network for common thorax disease classiﬁcation and reporting in chest x-rays.
DOI: 10.57702/zj2cjf2c
title: FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer

description: FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer