Results 11 to 20 of about 11,885,392 (298)
Semantic similarity dissociates shortfrom long-term recency effects: testing a neurocomputational model of list memory [PDF]
, 2006 The finding that recency effects can occur not only in immediate free recall (i.e., short-term recency) but also in the continuous-distractor task (i.e., long-term recency) has led many theorists to reject the distinction between short- and long-term ...
Usher, Marius +3 more
core +6 more sources
CoRR, 2021 This paper is based on a machine learning project at the Norwegian University of Science and Technology, fall 2020. The project was initiated with a literature review on the latest developments within time-series forecasting methods in the scientific community over the past five years.
Christian Bakke Vennerød +2 more
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Lipreading with long short-term memory [PDF]
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016 Accepted for publication at ICASSP ...
Michael Wand 0002 +2 more
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Quantum Long Short-Term Memory
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 Long short-term memory (LSTM) is a kind of recurrent neural networks (RNN) for sequence and temporal dependency data modeling and its effectiveness has been extensively established. In this work, we propose a hybrid quantum-classical model of LSTM, which we dub QLSTM.
Samuel Yen-Chi Chen +2 more
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, 2021 Long-term memory is the mechanism which enables us to store information and experiences in a lasting fashion, for possible retrieval at some point in the future. This ability to create and retrieve memories is fundamental to all aspects of cognition, and
Groome, D., Law, R.
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Forecasting Nonadiabatic Dynamics using Hybrid Convolutional Neural Network/Long Short-Term Memory Network [PDF]
, 2021 Modeling nonadiabatic dynamics in complex molecular or condensed-phase systems has been challenging especially for the long-time dynamics. In this work, we propose a time series machine learning scheme based on the hybrid convolutional neural network ...
Jiebo, Li +3 more
core +1 more source
Aircraft Gearbox Fault Diagnosis System: An Approach based on Deep Learning Techniques
Journal of Intelligent Systems, 2020 Gearbox is one of the vital components in aircraft engines. If any small damage to gearbox, it can cause the breakdown of aircraft engine. Thus it is significant to study fault diagnosis in gearbox system.
Mallikarjuna P B +3 more
doaj +1 more source
THE PSYCHOLINGUISTIC BASIS OF THE LINGUISTIC CONCEPTUALIZATION
Revista de Investigaciones Universidad del Quindío, 2022 The object of this article is the methodology of psycholinguistics concerning analyzing concepts. The article's relevance is due to the need to apply new approaches to linguistic phenomena analysis, for which a purely linguistic methodology is not
Zhao Yuanze +3 more
doaj +1 more source
Video Summarization with Long Short-Term Memory [PDF]
, 2016 We propose a novel supervised learning technique for summarizing videos by automatically selecting keyframes or key subshots. Casting the problem as a structured prediction problem on sequential data, our main idea is to use Long Short-Term Memory (LSTM), a special type of recurrent neural networks to model the variable-range dependencies entailed in ...
Ke Zhang 0028 +3 more
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