Results 51 to 60 of about 2,965,444 (278)
A labeled synthetic mobile money transaction datasetMendeley Data
Data in BriefThis data article introduces a labeled synthetic mobile money transaction dataset created using MoMTSim, a multi-agent-based simulation platform designed and validated specifically for mobile money transactions.
Denish Azamuke +2 more
doaj +1 more source
Learning From Labeled And Unlabeled Data: An Empirical Study Across Techniques And Domains
, 2011 There has been increased interest in devising learning techniques that combine unlabeled data with labeled data ? i.e. semi-supervised learning. However, to the best of our knowledge, no study has been performed across various techniques and different ...
Chawla, N. V., Karakoulas, Grigoris
core +1 more source
Mapping the evolution of mitochondrial complex I through structural variation
FEBS Letters, EarlyView.Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin +2 more
wiley +1 more source
Semi-Supervised Image Captioning by Adversarially Propagating Labeled Data
IEEE AccessWe present a novel data-efficient semi-supervised framework to improve the generalization of image captioning models. Constructing a large-scale labeled image captioning dataset is expensive in terms of labor, time, and cost.
Dong-Jin Kim +3 more
doaj +1 more source
FEBS Letters, EarlyView.Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho +3 more
wiley +1 more source
Pixel-Wise Defect Detection by CNNs without Manually Labeled Training Data
Applied Artificial Intelligence, 2019 In machine learning driven surface inspection one often faces the issue that defects to be detected are difficult to make available for training, especially when pixel-wise labeling is required.
M. Haselmann, D. P. Gruber
doaj +1 more source
Normalization of Microarray Data: Single-labeled and Dual-labeled Arrays
Molecules and Cells, 2006 DNA microarray is a powerful tool for high-throughput analysis of biological systems. Various computational tools have been created to facilitate the analysis of the large volume of data produced in DNA microarray experiments. Normalization is a critical step for obtaining data that are reliable and usable for subsequent analysis such as identification
Jin Hwan, Do, Dong-Kug, Choi
openaire +2 more sources
Learning safe multi-label prediction for weakly labeled data [PDF]
Machine Learning, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wei, Tong +3 more
openaire +2 more sources
Protein pyrophosphorylation by inositol pyrophosphates — detection, function, and regulation
FEBS Letters, EarlyView.Protein pyrophosphorylation is an unusual signaling mechanism that was discovered two decades ago. It can be driven by inositol pyrophosphate messengers and influences various cellular processes. Herein, we summarize the research progress and challenges of this field, covering pathways found to be regulated by this posttranslational modification as ...
Sarah Lampe +3 more
wiley +1 more source
BLAINDER—A Blender AI Add-On for Generation of Semantically Labeled Depth-Sensing Data
Sensors, 2021 Common Machine-Learning (ML) approaches for scene classification require a large amount of training data. However, for classification of depth sensor data, in contrast to image data, relatively few databases are publicly available and manual generation ...
Stefan Reitmann +2 more
doaj +1 more source