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Prospects of model predictive control of the drum level at a 225 MW combined cycle power plant
(Institute of Electrical and Electronics Engineers Inc., 2016-10)
We report the application of the Model-based Predictive Control (MPC) to improve the performance of the start-up of a 150-175 MW combined cycle power plant whose gas turbine is fueled by natural gas. In concrete the ...
Analyzing the effect of hyperparameters in a automobile classifier based on convolutional neural networks
(IEEE Computer Society, 2017)
In the recent years the convolutional neural network is used successfully in applications of image classification, due to its deep and hierarchical architecture. The hyper parameters of the convolutional neural networks ...
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 ...
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 ...
Convolutional neural networks ensembles through single-iteration optimization
(2022-01-01)
Convolutional Neural Networks have been widely employed in a diverse range of computer vision-based applications, including image classification, object recognition, and object segmentation. Nevertheless, one weakness of ...
Rank-based self-training for graph convolutional networks
(2021-03-01)
Graph Convolutional Networks (GCNs) have been established as a fundamental approach for representation learning on graphs, based on convolution operations on non-Euclidean domain, defined by graph-structured data. GCNs and ...
Separation dichotomy and wavefronts for a nonlinear convolution equation
(ACADEMIC PRESS INC ELSEVIER SCIENCE, 2014)
ENVIRONMENTAL MONITORING USING DRONE IMAGES AND CONVOLUTIONAL NEURAL NETWORKS
(Ieee, 2018-01-01)
Recently, drone images have been used in a number of applications, mainly for pollution control and surveillance purposes. In this paper, we introduce the well-known Convolutional Neural Networks in the context of environmental ...
Environmental monitoring using drone images and convolutional neural networks
(2018-10-31)
Recently, drone images have been used in a number of applications, mainly for pollution control and surveillance purposes. In this paper, we introduce the well-known Convolutional Neural Networks in the context of environmental ...