Results 21 to 30 of about 3,556 (261)

Hand Gesture Recognition Using Single Patchable Six-Axis Inertial Measurement Unit via Recurrent Neural Networks

open access: yesSensors, 2021
Recording human gestures from a wearable sensor produces valuable information to implement control gestures or in healthcare services. The wearable sensor is required to be small and easily worn.
Edwin Valarezo Añazco   +5 more
doaj   +1 more source

Less is More: Rethinking Few-Shot Learning and Recurrent Neural Nets

open access: yesCoRR, 2022
Version 3 is focused exclusively on the first part of v1 and v2, correcting minor mathematical errors.
Deborah Pereg   +3 more
openaire   +2 more sources

A hybrid model for fake news detection: Leveraging news content and user comments in fake news

open access: yesIET Information Security, 2021
Nowadays, social media platforms such as Twitter have become a popular medium for people to spread and consume news because of their easy access and the rapid proliferation of news.
Marwan Albahar
doaj   +1 more source

Graphical Analysis of the Progression of Atrial Arrhythmia Using Recurrent Neural Networks

open access: yesInternational Journal of Computational Intelligence Systems, 2020
Pacemaker logs are used to predict the progression of paroxysmal cardiac arrhythmia to permanent atrial fibrillation by means of different deep learning algorithms. Recurrent Neural Networks are trained on data produced by a generative model.
Nahuel Costa   +3 more
doaj   +1 more source

Siamese recurrent neural networks for the robust classification of grid disturbances in transmission power systems considering unknown events

open access: yesIET Smart Grid, 2022
The automated identification and localisation of grid disturbances is a major research area and key technology for the monitoring and control of future power systems.
André Kummerow   +2 more
doaj   +1 more source

Cross refinement network with edge detection for salient object detection

open access: yesIET Signal Processing, 2021
Salient object detection aims to identify the most attractive objects from images. However, their boundaries are typically of poor quality when predicted using available methods.
Junjiang Xiang   +4 more
doaj   +1 more source

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks [PDF]

open access: yesBiological Cybernetics, 2012
Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in ...
Sebastian Bitzer, Stefan J. Kiebel
openaire   +4 more sources

A BiLSTM cardinality estimator in complex database systems based on attention mechanism

open access: yesCAAI Transactions on Intelligence Technology, 2022
An excellent cardinality estimation can make the query optimiser produce a good execution plan. Although there are some studies on cardinality estimation, the prediction results of existing cardinality estimators are inaccurate and the query efficiency ...
Qiang Zhou   +8 more
doaj   +1 more source

A comprehensive framework from real‐time prognostics to maintenance decisions

open access: yesIET Collaborative Intelligent Manufacturing, 2021
Studying the influence of imperfect prognostics information on maintenance decisions is an underexplored area. To bridge this gap, a new comprehensive maintenance support system is proposed. First, a survival theory‐based prognostics module employing the
Amit Kumar Jain   +4 more
doaj   +1 more source

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