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Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement
Deep learning (DL) networks have grown into powerful alternatives for speech enhancement and have achieved excellent results by improving speech quality, intelligibility, and background noise suppression. Due to high ...
Deep Learning Methods for Forecasting COVID-19 Time-Series Data: A Comparative Study
The novel coronavirus (COVID-19) has significantly spread over the world and comes up with new challenges to the research community. Although governments imposing numerous containment and social distancing measures, the ...
G-Sep: A Deep Learning Algorithm for Detection of Long-Term Sepsis Using Bidirectional Gated Recurrent Unit
Sepsis is a common and deadly condition that must be treated eloquently within 19 hours. Numerous deep learning techniques, including Recurrent Neural Networks, Convolution Neural Networks, Long Short-Term Memory, and Gated ...
A Spatio-Temporal Attention Graph Convolutional Networks for Sea Surface Temperature Prediction
Sea surface temperature (SST) is an important index to detect ocean changes, predict SST anomalies, and prevent natural disasters caused by abnormal changes, dynamic variation of which have a profound impact on the whole ...
ConvGRU-CNN: Spatiotemporal Deep Learning for Real-World Anomaly Detection in Video Surveillance System
Video surveillance for real-world anomaly detection and prevention using deep learning is an important and difficult research area. It is imperative to detect and prevent anomalies to develop a nonviolent society. Realworld ...
Bag of Samplings for computer-assisted Parkinson's disease diagnosis based on Recurrent Neural Networks
(2019-12-01)
Parkinson's Disease (PD) is a clinical syndrome that affects millions of people worldwide. Although considered as a non-lethal disease, PD shortens the life expectancy of the patients. Many studies have been dedicated to ...
Diseño de una herramienta para la predicción, detección y corrección de fallos en propulsores con multirrotores
(Instituto Tecnológico de Costa Rica, 2020)
El presente documento es un informe final para optar por el título de licenciado en
ingeniería en mecatrónica, el cual presenta el desarrollo de un sistema capaz de detectar los fallos que se pueden presentar durante el ...
Um estudo de redes neurais recorrentes no contexto de previsões no mercado financeiro
(Universidade Federal de São CarlosUFSCarCâmpus São CarlosEngenharia de Computação - EC, 2020-12-17)
Financial time series forecasting is one of the most researched artificial intelligence applications by financial market analysts, both in the academic and corporate world. Within this area, there is a great emphasis on ...
Internacionalización de las empresas de Catering en el sector aerolíneas en el Perú: Caso Gate Gourmet
(Universidad Peruana de Ciencias Aplicadas (UPC)PE, 2018-03-03)
La presente investigación tiene por objetivo establecer y determinar las principales estrategias de internacionalización de las empresas dedicadas al rubro de catering aéreo en el país. Al ser este un rubro altamente ...
Comparativo entre redes neurais recorrentes GRU e LSTM para a predição de instrumentos financeiros
(Universidade Tecnológica Federal do ParanáMedianeiraBrasilCiência da ComputaçãoUTFPR, 2021-05-04)
This work aims to compare two models of recurrent neural networks, for the prediction of quotation of financial instruments, considering criteria such as coefficient of determination and correlation coefficient of predicted ...