Results 51 to 60 of about 2,406,574 (279)
Weather Classification by Utilizing Synthetic Data
Sensors, 2022 Weather prediction from real-world images can be termed a complex task when targeting classification using neural networks. Moreover, the number of images throughout the available datasets can contain a huge amount of variance when comparing locations ...
Saad Minhas +4 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
Nanoparticle Detection on SEM Images Using a Neural Network and Semi-Synthetic Training Data
Nanomaterials, 2022 Processing images represents a necessary step in the process of analysing the information gathered about nanoparticles after characteristic material samples have been scanned with electron microscopy, which often requires the use of image processing ...
Jorge David López Gutiérrez +2 more
doaj +1 more source
Modeling Camera Effects to Improve Visual Learning from Synthetic Data
, 2018 Recent work has focused on generating synthetic imagery to increase the size and variability of training data for learning visual tasks in urban scenes.
A Andreopoulos +10 more
core +1 more source
Phosphatidylinositol 4‐kinase as a target of pathogens—friend or foe?
FEBS Letters, EarlyView.This graphical summary illustrates the roles of phosphatidylinositol 4‐kinases (PI4Ks). PI4Ks regulate key cellular processes and can be hijacked by pathogens, such as viruses, bacteria and parasites, to support their intracellular replication. Their dual role as essential host enzymes and pathogen cofactors makes them promising drug targets.
Ana C. Mendes +3 more
wiley +1 more source
Nature CommunicationsRecent advances in tissue engineering have been remarkable, yet the precise control of cellular behavior in 2D and 3D cultures remains challenging.
Hannes M. Beyer +10 more
doaj +1 more source
Machine Learning and Knowledge Extraction, 2023 Data augmentation is an important procedure in deep learning. GAN-based data augmentation can be utilized in many domains. For instance, in the credit card fraud domain, the imbalanced dataset problem is a major one as the number of credit card fraud ...
Emilija Strelcenia, Simant Prakoonwit
doaj +1 more source
Generating Synthetic Data for Neural Keyword-to-Question Models
, 2018 Search typically relies on keyword queries, but these are often semantically ambiguous. We propose to overcome this by offering users natural language questions, based on their keyword queries, to disambiguate their intent.
Bogdanova Dasha +4 more
core +1 more source
Privacy of Synthetic Data: A Statistical Framework
IEEE Transactions on Information Theory, 2023 Privacy-preserving data analysis is emerging as a challenging problem with far-reaching impact. In particular, synthetic data are a promising concept toward solving the aporetic conflict between data privacy and data sharing. Yet, it is known that accurately generating private, synthetic data of certain kinds is NP-hard.
March Boedihardjo +2 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