Results 141 to 150 of about 59,151 (296)
MetaLab: Few-Shot Game Changer for Image Recognition
Difficult few-shot image recognition has significant application prospects, yet remaining the substantial technical gaps with the conventional large-scale image recognition. In this paper, we have proposed an efficient original method for few-shot image recognition, called CIELab-Guided Coherent Meta-Learning (MetaLab).
Chaofei Qi, Zhitai Liu, Jianbin Qiu
openaire +2 more sources
YIPFα1A expression is regulated by multilayered molecular mechanisms
YIPFα1A, a five‐pass Golgi protein, is regulated at multiple layers. (1) Rare‐codon enrichment drives translation‐coupled mRNA decay. (2) A proximal 3′‐UTR element stabilizes mRNA. (3) A distal 3′‐UTR element included by alternate poly(A) site usage represses translation, which can be overridden by the proximal 3′‐UTR element.
Tokio Takaji +2 more
wiley +1 more source
Few-shot Named Entity Recognition via encoder and class intervention
In the real world, the large and complex nature of text increases the difficulty of tagging and results in a limited amount of tagged text. Few-shot Named Entity Recognition(NER) only uses a small amount of annotation data to identify and classify ...
Long Ding +5 more
doaj +1 more source
Matching Compound Prototypes for Few-Shot Action Recognition
AbstractThe task of few-shot action recognition aims to recognize novel action classes using only a small number of labeled training samples. How to better describe the action in each video and how to compare the similarity between videos are two of the most critical factors in this task.
Yifei Huang 0002 +5 more
openaire +1 more source
The MRP4 transporter exports several drugs and signaling molecules. Here, we identified key promoter elements regulating basal MRP4 expression. Using reporter assays, we defined a conserved region with essential Sp1 and contributory Ets sites, which controlled basal MRP4 expression.
Debora Singer +7 more
wiley +1 more source
Few-Shot Learning Sensitive Recognition Method Based on Prototypical Network
Traditional machine learning-based entity extraction methods rely heavily on feature engineering by experts, and the generalization ability of the model is poor. Prototype networks, on the other hand, can effectively use a small amount of labeled data to
Guoquan Yuan +4 more
doaj +1 more source
Derivation and characterization of retinal pigment epithelium from urine‐derived iPSCs
Age‐related macular degeneration causes vision loss via RPE dysfunction and loss. Traditional iPSC therapies rely on invasive biopsies, limiting scalability. Here, we utilize urine‐derived stem cells as an accessible source to generate u‐iPSCs, successfully differentiated into pigmented RPE. This “Urine‐to‐Retina” platform provides a promising path for
Daniella Beiner +7 more
wiley +1 more source
Abruptly changing from aerobic to anaerobic conditions (sudden anaerobization) induced growth inhibition and a significant increase in intracellular labile ferrous iron in the aerotolerant anaerobe Amphibacillus xylanus. We found that free flavins mediate efficient electron transfer from NADH to ferric iron under anaerobic conditions, suggesting that ...
Shinya Kimata +13 more
wiley +1 more source
Few-Shot Face Recognition: Leveraging GAN for Effective Data Augmentation
Face recognition technology is a prominent research area in the digital age, with significant applications in commerce and security. This technology relies on high-quality training data, which poses a challenge in practical engineering applications owing
Cai Yue, Shuhui Li, Hang Zhou
core +1 more source
In normal (nontolerant) cells, CD14 is crucial for both LPS uptake and LPS signaling. In LPS‐tolerant cells, in which LPS‐induced TNF‐α and IFN‐β production is suppressed, there is a dramatic increase in surface CD14 expression. The overexpressed CD14 in LPS‐tolerant cells is responsible for the enhanced LPS uptake without inducing pro‐inflammatory ...
Saeka Nishihara +3 more
wiley +1 more source

