Results 41 to 50 of about 5,483,449 (298)
Gated Graph Convolutional Recurrent Neural Networks [PDF]
2019 27th European Signal Processing Conference (EUSIPCO), 2019 Graph processes model a number of important problems such as identifying the epicenter of an earthquake or predicting weather. In this paper, we propose a Graph Convolutional Recurrent Neural Network (GCRNN) architecture specifically tailored to deal with these problems.
Luana Ruiz +2 more
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Recurrent Convolutional Neural Networks for Scene Parsing
CoRR, 2013 Scene parsing is a technique that consist on giving a label to all pixels in an image according to the class they belong to. To ensure a good visual coherence and a high class accuracy, it is essential for a scene parser to capture image long range dependencies.
Pedro H. O. Pinheiro, Ronan Collobert
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Convolutional unitary or orthogonal recurrent neural networks
CoRR, 2023 Recurrent neural networks are extremely powerful yet hard to train. One of their issues is the vanishing gradient problem, whereby propagation of training signals may be exponentially attenuated, freezing training. Use of orthogonal or unitary matrices, whose powers neither explode nor decay, has been proposed to mitigate this issue, but their ...
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NLOS Identification in WLANs Using Deep LSTM with CNN Features
Sensors, 2018 Identifying channel states as line-of-sight or non-line-of-sight helps to optimize location-based services in wireless communications. The received signal strength identification and channel state information are used to estimate channel conditions for ...
Viet-Hung Nguyen +3 more
doaj +1 more source
JuTISI (Jurnal Teknik Informatika dan Sistem Informasi), 2020 Nowadays internet access is getting easier to get. Because of the ease of access to the internet, almost all internet users have social media. Social media is widely used by users to call out their opinions or even to make complaints about a matter and ...
Ivan Nathaniel Husada, Hapnes Toba
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Design and Development of RNN Anomaly Detection Model for IoT Networks
IEEE Access, 2022 Cybersecurity is important today because of the increasing growth of the Internet of Things (IoT), which has resulted in a variety of attacks on computer systems and networks. Cyber security has become an increasingly difficult issue to manage as various
Imtiaz Ullah, Qusay H. Mahmoud
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Convolutional Recurrent Neural Networks for Electrocardiogram Classification
Computing in Cardiology Conference (CinC), 2017 We propose two deep neural network architectures for classification of arbitrary-length electrocardiogram (ECG) recordings and evaluate them on the atrial fibrillation (AF) classification data set provided by the PhysioNet/CinC Challenge 2017. The first architecture is a deep convolutional neural network (CNN) with averaging-based feature aggregation ...
Martin Zihlmann +2 more
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Applications of recurrent neural networks in batch reactors. Part I: NARMA modelling of the dynamic behaviour of the heat transfer fluid [PDF]
, 1997 This paper is focused on the development of nonlinear models, using artificial neural networks, able to provide appropriate predictions when acting as process simulators. The dynamic behaviour of the heat transfer fluid temperature in a jacketed chemical
J.M. Zaldı́var +3 more
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Convolutional recurrent neural networks for bird audio detection [PDF]
2017 25th European Signal Processing Conference (EUSIPCO), 2017 Publication in the conference proceedings of EUSIPCO, Kos island, Greece ...
Emre Cakir +4 more
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Exponential stability of delayed recurrent neural networks with Markovian jumping parameters [PDF]
, 2006 This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2006 Elsevier Ltd.In this Letter, the global exponential stability analysis problem is considered for a class of recurrent ...
Liu, Y, Yu, L, Wang, Z, Iu, X
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