Results 121 to 130 of about 31,081 (304)
Distance Based Korean WordNet(alias. KorLex) Embedding Model
Applied Artificial IntelligenceThe objective of this study was to create graph embedding vectors using Korean WordNet (KorLex) and apply them to neural network word-embedding models.
SeongReol Park +4 more
doaj +1 more source
Plasmonic Enhancement of Fluorescence and Protein Dynamics in Living Mammalian Cells
Advanced Materials, EarlyView.This study demonstrates plasmonic enhancement of the function of fluorescent voltage sensing proteins (genetically encoded voltage indicators, (GEVIs), QuasAr6) in live mammalian cells. Coupling to plasmonic nanoparticles does not just increase fluorescence, but influences the protein photocycle, creating a hybrid sensor with its response speed to ...
Marco Locarno +16 more
wiley +1 more source
A Study on Word2Vec on a Historical Swedish Newspaper Corpus
Digital Humanities in the Nordic and Baltic Countries Publications, 2018 Detecting word sense changes can be of great interest in the field of digital humanities. Thus far, most investigations and automatic methods have been developed and carried out on English text and most recent methods make use of word embeddings.
Nina Tahmasebi
doaj +1 more source
, 2023 Word embedding has become ubiquitous and is widely used in various natural language processing (NLP) tasks, such as web retrieval, web semantic analysis, and machine translation, and so on. Unfortunately, training the word embedding in a relatively large
Chen, Huacan +6 more
core
Word embedding based on low-rank doubly stochastic matrix decomposition [PDF]
, 2018 Word embedding, which encodes words into vectors, is an important starting point in natural language processing and commonly used in many text-based machine learning tasks.
Yang, Zhirong, Sedov, Denis
core +1 more source
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
Advanced Materials, EarlyView.This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
Post-processing Techniques for Word Embedding
Word embedding has been a significant breakthrough in natural language processing (NLP). Although word representation has improved remarkably and resulted in better performance in downstream NLP applications, interpretability of word embeddings remains a
Albujasim, Zainab Majeed
core +1 more source
Angular-Based Word Meta-Embedding Learning [PDF]
, 2018 Ensembling word embeddings to improve distributed word representations has shown good success for natural language processing tasks in recent years. These approaches either carry out straightforward mathematical operations over a set of vectors or use ...
Neill, James O', Bollegala, Danushka
core
Advanced Materials, EarlyView.AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
IEEE AccessDiversity in use of Question and Answering (Q/A) is evolving as a popular application in the area of Natural Language Processing (NLP). The alive unsupervised word embedding approaches are efficient to collect Latent-Semantic data on number of tasks. But
M. Suguna, K. S. Sakunthala Prabha
doaj +1 more source