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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 ...
A Novel Binary Emperor Penguin Optimizer for Feature Selection Tasks
(Tech Science Press, 2022)
Nowadays, due to the increase in information resources, the number of parameters and complexity of feature vectors increases. Optimization methods offer more practical solutions instead of exact solutions for the solution ...
Class-driven content-based medical image retrieval using hash codes of deep features
(Elsevier Sci Ltd, 2021)
Medical imaging provides the convenience of physicians to analyze the disease by providing visual data of the body parts required for clinical research and treatment. Today, increasing medical images following technological ...
Automatic Detection of Power Quality Disturbance Using Convolutional Neural Network Structure with Gated Recurrent Unit
(Hindawi Ltd, 2021)
Power quality disturbance (PQD) is essential for devices consuming electricity and meeting today's energy trends. This study contains an effective artificial intelligence (AI) framework for analyzing single or composite ...
Focal modulation network for lung segmentation in chest X-ray images
(Tubitak Scientific & Technological Research Council Turkey, 2023)
Segmentation of lung regions is of key importance for the automatic analysis of Chest X-Ray (CXR) images, which have a vital role in the detection of various pulmonary diseases. Precise identification of lung regions is ...
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 ...
Focal Modulation Based End-to-End Multi-Label Classification for Chest X-ray Image Classification
(Ieee, 2023)
Chest X-ray imaging is of critical importance in order to effectively diagnose chest diseases, which are increasing today due to various environmental and hereditary factors. Although chest X-ray is the most commonly used ...
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 ...
Content-based medical image retrieval with opponent class adaptive margin loss
(Elsevier Science Inc, 2023)
The increasing utilization of medical imaging technology with digital storage capabilities has facilitated the compilation of large-scale data repositories. Fast access to image samples with similar appearance to suspected ...
