Yazar "Ozturk, Saban" için Scopus İndeksli Yayınlar Koleksiyonu listeleme
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An adaptive deep learning framework to classify unknown composite power quality event using known single power quality events
Sindi, Hatem; Nour, Majid; Rawa, Muhyaddin; Ozturk, Saban; Polat, Kemal (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 ... -
Adaptive diffusion priors for accelerated MRI reconstruction
Gungor, Alper; Dar, Salman U. H.; Ozturk, Saban; Korkmaz, Yilmaz; Bedel, Hasan A.; Elmas, Gokberk; Ozbey, Muzaffer (Elsevier, 2023)Deep MRI reconstruction is commonly performed with conditional models that de-alias undersampled acquisitions to recover images consistent with fully-sampled data. Since conditional models are trained with knowledge of the ... -
Attention-based end-to-end CNN framework for content-based X-ray image retrieval
Ozturk, Saban; Alhudhaif, Adi; Polat, Kemal (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 ... -
Automatic Detection of Power Quality Disturbance Using Convolutional Neural Network Structure with Gated Recurrent Unit
Yigit, Enes; Ozkaya, Umut; Ozturk, Saban; Singh, Dilbag; Gritli, Hassene (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 ... -
Class-driven content-based medical image retrieval using hash codes of deep features
Ozturk, Saban (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 ... -
Comparative Regression Analysis for Estimating Resonant Frequency of C-Like Patch Antennas
Ozkaya, Umut; Yigit, Enes; Seyfi, Levent; Ozturk, Saban; Singh, Dilbag (Hindawi Ltd, 2021)This study provides a comparative analysis of regression techniques to estimate the operating frequency of the C-like microstrip antenna. The performance of well-known regression techniques such as linear regression (LR), ... -
Content-based medical image retrieval with opponent class adaptive margin loss
Ozturk, Saban; Celik, Emin; Cukur, Tolga (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 ... -
Convolutional neural network based dictionary learning to create hash codes for content-based image retrieval
Ozturk, Saban (Elsevier Science Bv, 2021)This study investigates the suitability of sparse vectors in the dictionary learning (DL) method for content-based image retrieval (CBIR) tasks. Since DL usually performs the learning process in an unsupervised manner, it ... -
An effective hashing method using W-Shaped contrastive loss for imbalanced datasets
Alenezi, Fayadh; Ozturk, Saban; Armghan, Ammar; Polat, Kemal (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 ... -
Focal Modulation Based End-to-End Multi-Label Classification for Chest X-ray Image Classification
Ozturk, Saban; Cukur, Tolga (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 ... -
Focal modulation network for lung segmentation in chest X-ray images
Ozturk, Saban; Cukur, Tolga (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 ... -
Hash Code Generation using Deep Feature Selection Guided Siamese Network for Content-Based Medical Image Retrieval
Ozturk, Saban (Gazi Univ, 2021)It is very pleasing for human health that medical knowledge has increased and the technological infrastructure improves medical systems. The widespread use of medical imaging devices has been instrumental in saving lives ... -
A Novel Binary Emperor Penguin Optimizer for Feature Selection Tasks
Kalra, Minakshi; Kumar, Vijay; Kaur, Manjit; Idris, Sahar Ahmed; Ozturk, Saban; Alshazly, Hammam (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 ... -
A novel classification framework using multiple bandwidth method with optimized CNN for brain-computer interfaces with EEG-fNIRS signals
Nour, Majid; Ozturk, Saban; Polat, Kemal (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
Sindi, Hatem; Nour, Majid; Rawa, Muhyaddin; Ozturk, Saban; Polat, Kemal (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 ... -
Random fully connected layered 1D CNN for solving the Z-bus loss allocation problem
Sindi, Hatem; Nour, Majid; Rawa, Muhyaddin; Ozturk, Saban; Polat, Kemal (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 ... -
Residual CNN plus Bi-LSTM model to analyze GPR B scan images
Ozkaya, Umut; Ozturk, Saban; Melgani, Farid; Seyfi, Levent (Elsevier, 2021)In this study, the residual Convolutional Neural Network (CNN) with the Bidirectional Long Short Time Memory (Bi-LSTM) model has proposed for the analysis of Ground Penetrating Radar B scan (GPR B Scan) images. GPR ... -
Residual LSTM layered CNN for classification of gastrointestinal tract diseases
Ozturk, Saban; Ozkaya, Umut (Academic Press Inc Elsevier Science, 2021)nowadays, considering the number of patients per specialist doctor, the size of the need for automatic medical image analysis methods can be understood. These systems, which are very advantageous compared to manual systems ... -
Reverse gamma correction based GARCH model for underwater image dehazing and detail exposure
Alenezi, Fayadh; Armghan, Ammar; Alharbi, Abdullah G.; Ozturk, Saban; Althubiti, Sara A.; Mansour, Romany F. (Pergamon-Elsevier Science Ltd, 2023)Underwater imaging poses significant challenges as water alters the behavior of light in comparison to air or vacuum. Therefore, it is crucial to effectively utilize the unique characteristics of unclear edges in hazy ... -
Unsupervised Medical Image Translation With Adversarial Diffusion Models
Ozbey, Muzaffer; Dalmaz, Onat; Dar, Salman U. H.; Bedel, Hasan A.; Ozturk, Saban; Gungor, Alper; Cukur, Tolga (Ieee-Inst Electrical Electronics Engineers Inc, 2023)Imputation of missing images via source-to-target modality translation can improve diversity in medical imaging protocols. A pervasive approach for synthesizing target images involves one-shot mapping through generative ...