Results 31 to 40 of about 1,496,086 (365)

Preregistered Replication of the Auditory Deviant Effect: A Robust Benchmark Finding

open access: yesJournal of Cognition, 2019
Short-term memory of visually presented lists of items is disrupted by auditory distraction. The auditory deviant effect refers to the finding that a sequence in which a single auditory event deviates from all other auditory objects disrupts serial ...
Raoul Bell   +4 more
doaj   +1 more source

Fluctuations of Attention and Working Memory

open access: yesJournal of Cognition, 2019
Attention and working memory are intricately related, yet there remain ambiguities in how to best characterize this relationship. In his review, Oberauer formalizes several dimensions for the relationship between attention and working memory, focusing ...
Kirsten C.S. Adam   +1 more
doaj   +1 more source

A Short Review About Working Memory

open access: yesAnkara Üniversitesi Tıp Fakültesi Mecmuas, 2021
The working memory system is responsible for the protection of limited information that can be kept in mind at once. Discussions on the existence of different circuits for different working memory, the limit of working memory and its developability are ...
Evrim Gökçe   +2 more
doaj   +1 more source

Prediction of Daily Climate Using Long Short-Term Memory (LSTM) Model

open access: yesInternational Journal of Innovative Science and Research Technology
Climaate prediction plays a vital role in various sectors, including agriculture, disaster management, and urban planning. Traditional methods for climate forecasting often rely on complex physical models, which require substantial computational ...
Jinxin Xu   +4 more
semanticscholar   +1 more source

A deep learning framework for financial time series using stacked autoencoders and long-short term memory

open access: yesPLoS ONE, 2017
The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long ...
Wei Bao, Jun Yue, Yulei Rao
semanticscholar   +1 more source

Transition-Based Dependency Parsing with Stack Long Short-Term Memory [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2015
This work was sponsored in part by the U. S. Army Research Laboratory and the U. S. Army Research Office/nunder contract/grant number W911NF-10-1-0533, and in part by NSF CAREER grant IIS-1054319./nMiguel Ballesteros is supported by the European ...
Chris Dyer   +4 more
semanticscholar   +1 more source

The Neuroanatomical, Neurophysiological and Psychological Basis of Memory: Current Models and Their Origins

open access: yesFrontiers in Pharmacology, 2017
This review aims to classify and clarify, from a neuroanatomical, neurophysiological, and psychological perspective, different memory models that are currently widespread in the literature as well as to describe their origins.
Eduardo Camina   +2 more
doaj   +1 more source

The Impact of Developing Short-Term Memory on the Interpretation Performance of Students

open access: yesCihan University-Erbil Journal of Humanities and Social Sciences, 2022
      This paper is concentrated on the impacts of short-term memory development techniques on students’ performance in interpretation courses. Subjects of the study are chosen among senior students of the Translation Department, Cihan University-Erbil.
Fereydoon Rasouli
doaj   +1 more source

Hierarchical Memory Matching Network for Video Object Segmentation [PDF]

open access: yesarXiv, 2021
We present Hierarchical Memory Matching Network (HMMN) for semi-supervised video object segmentation. Based on a recent memory-based method [33], we propose two advanced memory read modules that enable us to perform memory reading in multiple scales while exploiting temporal smoothness.
arxiv  

Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting

open access: yesWater, 2019
Flood forecasting is an essential requirement in integrated water resource management. This paper suggests a Long Short-Term Memory (LSTM) neural network model for flood forecasting, where the daily discharge and rainfall were used as input data ...
Xuan-Hien Le   +3 more
semanticscholar   +1 more source

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