Results 61 to 70 of about 1,741,359 (199)
Detecting fake speech in voice-based authentication systems is crucial for reliability. Traditional methods often struggle because they can't handle the complex patterns over time.
Arsalan R. Mirza +1 more
doaj +1 more source
Short-term load forecasting is viewed as one promising technology for demand prediction under the most critical inputs for the promising arrangement of power plant units.
Lichao Sun +4 more
doaj +1 more source
Parallelizable Stack Long Short-Term Memory [PDF]
Stack Long Short-Term Memory (StackLSTM) is useful for various applications such as parsing and string-to-tree neural machine translation, but it is also known to be notoriously difficult to parallelize for GPU training due to the fact that the computations are dependent on discrete operations.
Ding, Shuoyang, Koehn, Philipp
openaire +2 more sources
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
Short-term Load Forecasting with Distributed Long Short-Term Memory
5 pages, 4 figures, 2023 ISGT ...
Dong, Yi +3 more
openaire +2 more sources
Implication of GluR2 subunit of AMPA receptor in RGS14(414)-mediated memory enhancement [PDF]
Ongoing quest for finding treatment against memory loss seen in aging and in many neurological and neurodegenerative diseases, so far has been unsuccessful and memory enhancers are seen as a potential remedy against this brain dysfunction.
Bashir, Zafar I. +3 more
core
Lattice Long Short-Term Memory for Human Action Recognition
Human actions captured in video sequences are three-dimensional signals characterizing visual appearance and motion dynamics. To learn action patterns, existing methods adopt Convolutional and/or Recurrent Neural Networks (CNNs and RNNs).
Chen, Kevin +5 more
core +1 more source
Simulation and Empirical Studies of Long Short-Term Memory Performance to Deal with Limited Data
This research is proposed to determine the performance of time series machine learning in the presence of noise, where this approach is intended to forecast time series data.
Khusnia Nurul Khikmah +2 more
doaj +1 more source
The Short Term Memory Structure In State-Of-The Art Recall/Recognition Experiments of Rubin, Hinton and Wentzel [PDF]
Properties of a short term memory structure are discovered in the data of Rubin, Hinton and Wenzel (1999): Recall (recognition) probabilities and search times are linearly related through stimulus presentation lags from 6 seconds to 600 (350) seconds ...
Tarnow, Dr. Eugen
core

