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Toplam kayıt 6, listelenen: 1-6
Random fully connected layered 1D CNN for solving the Z-bus loss allocation problem
(Elsevier Sci Ltd, 2021)
Power loss allocation methods should be efficient enough to meet the needs of the customers on the bus and effectively calculate the losses from generators and consumers. In order to perform these tasks, a highly robust ...
Attention-based end-to-end CNN framework for content-based X-ray image retrieval
(Tubitak Scientific & Technological Research Council Turkey, 2021)
The widespread use of medical imaging devices allows deep analysis of diseases. However, the task of examining medical images increases the burden of specialist doctors. Computer-assisted systems provide an effective ...
An adaptive deep learning framework to classify unknown composite power quality event using known single power quality events
(Pergamon-Elsevier Science Ltd, 2021)
Distributed generation (DG) sources are preferred to meet today's energy needs effectively. The addition of many different types of renewable energy sources to the grid causes various problems in signal quality. Detection ...
A novel classification framework using multiple bandwidth method with optimized CNN for brain-computer interfaces with EEG-fNIRS signals
(Springer London Ltd, 2021)
The most effective way to communicate between the brain and electronic devices in the outside world is the brain-computer interface (BCI) systems. BCI systems use signals of being through neural activity in the brain to ...
A novel hybrid deep learning approach including combination of 1D power signals and 2D signal images for power quality disturbance classification
(Pergamon-Elsevier Science Ltd, 2021)
As a result of the widespread use of power electronic equipment and the increase in consumption, the importance of effective energy policies and the smart grid begins to increase. Nonlinear loads and other loads in electric ...
An effective hashing method using W-Shaped contrastive loss for imbalanced datasets
(Pergamon-Elsevier Science Ltd, 2022)
The extraction of informative features from medical images and the retrieving of similar images from data repositories is vital for clinical decision support systems. Unlike general tasks such as medical image classification ...