Results 51 to 60 of about 431,572 (197)
, 2021 The right choice of features to be extracted from individual or aggregated observations is an extremely critical factor for the success of modern network traffic classification approaches based on machine learning. Such activity, usually in charge of the
D’Angelo, Gianni, Palmieri, Francesco
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GCRINT: Network Traffic Imputation Using Graph Convolutional Recurrent Neural Network
ICC 2021 - IEEE International Conference on Communications, 2021 Missing values appear in most multivariate time series, especially in the monitored network traffic data due to high measurement cost and unavoidable loss.
Van An Le +5 more
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Learning Spatial Relations with a Standard Convolutional Neural Network [PDF]
, 2020 This paper shows how a standard convolutional neural network (CNN) without recurrent connections is able to learn general spatial relationships between different objects in an image.
Swingler, Kevin +3 more
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Multimodal Physiological Signal Emotion Recognition Based on Convolutional Recurrent Neural Network
IOP Conference Series: Materials Science and Engineering, 2020 In order to solve the problem that the emotion recognition rate of single-mode physiological signals is not high in the physiological signals based emotion recognition, in this paper, we propose a convolutional recurrent neural network based method for ...
J.B. Liao +3 more
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Polyphonic pitch detection with convolutional recurrent neural networks
CoRR, 2022 MIREX ...
Carl Thomé, Sven Ahlbäck
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Bearing Life Prediction Method Based on Parallel Multichannel Recurrent Convolutional Neural Network
, 2021 To extract the time-series characteristics of the original bearing signals and predict the remaining useful life (RUL) more effectively, a parallel multichannel recurrent convolutional neural network (PMCRCNN) is proposed for the prediction of RUL ...
Wenhao Xiong +3 more
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Music Artist Classification with Convolutional Recurrent Neural Networks [PDF]
2019 International Joint Conference on Neural Networks (IJCNN), 2019 Previous attempts at music artist classification use frame level audio features which summarize frequency content within short intervals of time. Comparatively, more recent music information retrieval tasks take advantage of temporal structure in audio spectrograms using deep convolutional and recurrent models. This paper revisits artist classification
Zain Nasrullah, Yue Zhao 0016
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IEEE Access, 2019 Speech is the most effective way for people to exchange complex information. Recognition of emotional information contained in speech is one of the important challenges in the field of artificial intelligence.
Pengxu Jiang +4 more
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Graph-Partitioning-Based Diffusion Convolutional Recurrent Neural Network for Large-Scale Traffic Forecasting [PDF]
Transportation Research Record, 2019 Traffic forecasting approaches are critical to developing adaptive strategies for mobility. Traffic patterns have complex spatial and temporal dependencies that make accurate forecasting on large highway networks a challenging task.
Tanwi Mallick +3 more
semanticscholar +1 more source
Recurrent Convolutional Neural Networks for Discourse Compositionality
CoRR, 2013 The compositionality of meaning extends beyond the single sentence. Just as words combine to form the meaning of sentences, so do sentences combine to form the meaning of paragraphs, dialogues and general discourse. We introduce both a sentence model and a discourse model corresponding to the two levels of compositionality.
Kalchbrenner, N, Blunsom, P
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