Results 31 to 40 of about 182,172 (303)
Ground-truth (GT) and predictions in Split 3 of FluentSigners-50 for SLR.
, 2022 Ground-truth (GT) and predictions in Split 3 of FluentSigners-50 for SLR.
Vadim Kimmelman (8921639) +5 more
core +1 more source
Evaluating explainability for graph neural networks
Scientific Data, 2023 As explanations are increasingly used to understand the behavior of graph neural networks (GNNs), evaluating the quality and reliability of GNN explanations is crucial.
Chirag Agarwal +3 more
doaj +1 more source
A Unified Framework for Graph-Based Multi-View Partial Multi-Label Learning
IEEE Access, 2023 Multi-view partial multi-label learning (MVPML) is a fundenmental problem where each sample is linked to multiple kinds of features and candidate labels, including ground-truth and noise labels.
Jiazheng Yuan +3 more
doaj +1 more source
Empirical methodology for crowdsourcing ground truth [PDF]
Semantic Web, 2021 The process of gathering ground truth data through human annotation is a major bottleneck in the use of information extraction methods for populating the Semantic Web. Crowdsourcing-based approaches are gaining popularity in the attempt to solve the issues related to volume of data and lack of annotators.
Dumitrache, Anca +6 more
openaire +3 more sources
, 2021 The ground truth genes contained within each ground truth set. (RTF)
Akul Singhania (502117) +3 more
core +1 more source
A Newly Developed Ground Truth Dataset for Visual Saliency in Videos
IEEE Access, 2018 Visual saliency models aim to detect important and eye catching portions in a scene by exploiting human visual system characteristics. The effectiveness of visual saliency models is evaluated by comparing saliency maps with a ground truth data set.
Muhammad Zeeshan +5 more
doaj +1 more source
Ground-truth labeling and inferred detections for images with high complexity.
, 2021 Comparison between the ground truth and the inferred detections in high-complexity images. On the left is an image labeled by a medical expert. The results of the trained model are provided on the right. (TIF)
Leonardo Vanneschi (11767436) +6 more
core +1 more source
HMPLMD: Handwritten Malayalam palm leaf manuscript dataset
Data in Brief, 2023 The realization of high recognition rates of degraded documents such as palm leaf manuscripts primarily relies on document enhancement. Advancement of deep learning models in the process of document enhancement plays a major role among non-deep learning ...
B.J. Bipin Nair, N. Shobha Rani
doaj +1 more source
Upscaling Evapotranspiration from a Single-Site to Satellite Pixel Scale
Remote Sensing, 2021 It is of great significance for the validation of remotely sensed evapotranspiration (ET) products to solve the spatial-scale mismatch between site observations and remote sensing estimations.
Xiang Li +11 more
doaj +1 more source
Synthetic microbleeds generation for classifier training without ground truth
, 2021 BACKGROUND AND OBJECTIVE: Cerebral microbleeds (CMB) are important biomarkers of cerebrovascular diseases and cognitive dysfunctions. Susceptibility weighted imaging (SWI) is a common MRI sequence where CMB appear as small hypointense blobs.
Fazlollahi, Amir +8 more
core +1 more source