Results 41 to 50 of about 37,616 (181)
Electronics Letters, 2023 The vector parabolic equation (VPE) method has been widely applied to the modelling of radio wave propagation in tunnel environments. However, dense spatial discretizations are generally required for VPE simulations to achieve acceptable accuracy.
Hao Qin, Siyi Huang, Xingqi Zhang
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Recurrent backpropagation and the dynamical approach to adaptive neural computation [PDF]
, 1989 Error backpropagation in feedforward neural network models is a popular learning algorithm that has its roots in nonlinear estimation and optimization.
Pineda, Fernando J.
core
Two-Stream RNN/CNN for Action Recognition in 3D Videos
, 2018 The recognition of actions from video sequences has many applications in health monitoring, assisted living, surveillance, and smart homes. Despite advances in sensing, in particular related to 3D video, the methodologies to process the data are still ...
Ali, Haider +2 more
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Few‐label aerial target intention recognition based on self‐supervised contrastive learning
IET Radar, Sonar & NavigationIdentifying the intentions of aerial targets is crucial for air situation understanding and decision making. Deep learning, with its powerful feature learning and representation capability, has become a key means to achieve higher performance in aerial ...
Zihao Song +5 more
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Deep learning for day-ahead electricity price forecasting
IET Smart Grid, 2020 Deregulation exposes the inherent volatility of the electricity price. Accurate electricity price forecasting (EPF) could help the market participants to hedge against the price movements and maximise their profits.
Chi Zhang +4 more
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Deep Architectures and Ensembles for Semantic Video Classification [PDF]
, 2018 This work addresses the problem of accurate semantic labelling of short videos. To this end, a multitude of different deep nets, ranging from traditional recurrent neural networks (LSTM, GRU), temporal agnostic networks (FV,VLAD,BoW), fully connected ...
Bober, Miroslaw +3 more
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An associative memory for the on-line recognition and prediction of temporal sequences
, 2005 This paper presents the design of an associative memory with feedback that is capable of on-line temporal sequence learning. A framework for on-line sequence learning has been proposed, and different sequence learning models have been analysed according ...
Bose, J., Furber, S. B., Shapiro, J. L.
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English Conversational Telephone Speech Recognition by Humans and Machines
, 2017 One of the most difficult speech recognition tasks is accurate recognition of human to human communication. Advances in deep learning over the last few years have produced major speech recognition improvements on the representative Switchboard ...
Audhkhasi, Kartik +11 more
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Adversarial Generation of Natural Language
, 2017 Generative Adversarial Networks (GANs) have gathered a lot of attention from the computer vision community, yielding impressive results for image generation.
Courville, Aaron +4 more
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Local feature‐based video captioning with multiple classifier and CARU‐attention
IET Image ProcessingVideo captioning aims to identify multiple objects and their behaviours in a video event and generate captions for the current scene. This task aims to generate a detailed description of the current video in real‐time using natural language, which ...
Sio‐Kei Im, Ka‐Hou Chan
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