Results 131 to 140 of about 59,151 (296)
CLIP-Vision Guided Few-Shot Metal Surface Defect Recognition
Metal surface defect recognition (MSDR) based on deep learning encounters the challenge of few-shot expert-labeled data. In this study, we proposed a CLIP-vision guided self supervised learning (CVGSSL) framework for representation learning of unlabeled ...
Piuri, Vincenzo +9 more
core +1 more source
MiR‐513a promotes human erythroid differentiation by modulating c‐Jun
During early human erythropoiesis, miR‐513a promoted erythroid differentiation in primary human CD34+ hematopoietic stem‐progenitor cells and human TF‐1 erythroleukemic cells by indirectly decreasing c‐Jun and phospho‐c‐Jun expression, which are associated with increased GATA1 expression.
MinJung Kim +11 more
wiley +1 more source
LLM-Augmented Prototype Representation for Few-Shot Named-Entity Recognition
Named Entity Recognition (NER) models face challenges in adapting to data distribution shifts, especially with unseen entity types and limited data. Few-shot learning is used to address long-tailed distributions and unseen classes, but struggles with few
Weerayut Buaphet +4 more
doaj +1 more source
Rapid screening of staphylokinase protein variants using an unpurified cell‐free expression system
An unpurified cell‐free protein synthesis (CFPS) platform enables rapid functional screening of staphylokinase variants. Direct plasminogen‐activation assays performed in microplate format provide real‐time activity readouts, allowing rapid identification and ranking of variants with improved or reduced fibrinolytic activity without protein ...
Maria Tomková +3 more
wiley +1 more source
Class-Incremental Learning-Based Few-Shot Underwater-Acoustic Target Recognition
This paper proposes an underwater-acoustic class-incremental few-shot learning (UACIL) method for streaming data processing in practical underwater-acoustic target recognition scenarios. The core objective is to expand classification capabilities for new
Wenbo Wang +3 more
doaj +1 more source
Reconstruction guided Meta-learning for Few Shot Open Set Recognition
In many applications, we are constrained to learn classifiers from very limited data (few-shot classification). The task becomes even more challenging if it is also required to identify samples from unknown categories (open-set classification).
Roy-Chowdhury, Amit K. +3 more
core
Evolutionarily divergent DUF4465 domains have a common vitamin B12‐binding function
We show that DUF4465 family proteins, widespread across bacteria from gut microbiomes, hydrothermal vents, and soil, share a common vitamin B12‐binding function. These augmented β‐jellyroll proteins bind vitamin B12 via extended loops. Our findings establish sequence‐diverse DUF4465 proteins as a widespread class of B12‐binding proteins, highlighting ...
Charlea Clarke +4 more
wiley +1 more source
Integrative Few-Shot Learning for Classification and Segmentation
We introduce the integrative task of few-shot classification and segmentation (FS-CS) that aims to both classify and segment target objects in a query image when the target classes are given with a few examples.
강다현, 조민수
core
Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane +11 more
wiley +1 more source
Task-Adaptive Multi-Source Representations for Few-Shot Image Recognition
Conventional few-shot learning (FSL) mainly focuses on knowledge transfer from a single source dataset to a recognition scenario with only a few training samples available but still similar to the source domain.
Ge Liu +2 more
doaj +1 more source

