Browsing Computer Engineering by Department "İstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü"
Now showing items 1-15 of 15
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Analysis of deep learning based path loss prediction from satellite images
(Institute of Electrical and Electronics Engineers Inc., 2021)Determining the channel model parameters of a wireless communication system, either by measurements or by running electromagnetic propagation simulations, is a time-consuming process. Any rapid deployment of network demands ... -
Brain tumor classification using MRI images and convolutional neural networks
(Institute of Electrical and Electronics Engineers Inc., 2022)The brain tumor has become one of the most prominent types of cancers affecting a huge population across the globe every year. It has the lowest life expectancy rate and the risk of death is highly associated with the type, ... -
Deep learning-based blind image super-resolution using iterative networks
(Institute of Electrical and Electronics Engineers Inc., 2021)Deep learning-based single image super-resolution (SR) consistently shows superior performance compared to the traditional SR methods. However, most of these methods assume that the blur kernel used to generate the ... -
Geniş alan görüntülerinde anomali tespiti
(Institute of Electrical and Electronics Engineers Inc., 2021)Bu çalışma hava araçlarından çekilmiş geniş alan görüntülerindeki anomalileri tespit etmek ile ilgilidir. Anomali kümesi normal seyrin dışındaki her şey olarak belirlenmiştir. Bu amaçla iki farklı veri seti kullanılmış ve ... -
HM-net: A regression network for object center detection and tracking on wide area motion imagery
(IEEE-Institute of Electrical and Electronics Engineers Inc., 2022)Wide Area Motion Imagery (WAMI) yields high resolution images with a large number of extremely small objects. Target objects have large spatial displacements throughout consecutive frames. This nature of WAMI images makes ... -
Improved YOLOv4 for aerial object detection
(Institute of Electrical and Electronics Engineers Inc., 2021)Drones equipped with cameras are being used for surveillance purposes. These surveillance systems need vision-based object detection of ground objects which look very small because of the altitude of drones. We propose an ... -
In silico analysis of a highly mutated gene in cancer provides insight into abnormal mRNA splicing: Splicing factor 3B subunit 1k700e mutant
(MDPI AG, 2020)Cancer is the second leading cause of death worldwide. The etiology of the disease has remained elusive, but mutations causing aberrant RNA splicing have been considered one of the significant factors in various cancer ... -
Infrared-to-optical image translation for keypoint-based image registration
(Institute of Electrical and Electronics Engineers Inc., 2022)Multi-modal image registration is a critical step in many remote sensing and visual navigation applications. While image registration techniques developed for single modality images do not perform well for multi-modal ... -
Iterative kernel reconstruction for deep learning-based blind image super-resolution
(IEEE Computer Society, 2022)Deep learning based methods have received a great deal of interest in recent years to solve the single image superresolution (SISR) problem and their performance is proven to be superior when compared to classical SR ... -
Low-complexity deep learning-based beamforming in MISO systems
(Institute of Electrical and Electronics Engineers Inc., 2021)This study proposes a low-complexity deep learning-based beamforming neural network (BFNN) for massive multiple-input single-output (MISO) systems. We adopt an unsupervised learning-based convolutional neural network (CNN) ... -
PL-GAN: Path loss prediction using generative adversarial networks
(IEEE-Institute of Electrical and Electronics Engineers Inc., 2022)Accurate prediction of path loss is essential for the design and optimization of wireless communication networks. Existing path loss prediction methods typically suffer from the trade-off between accuracy and computational ... -
Predicting path loss distribution of an area from satellite ımages using deep learning
(IEEE - Institute of Electrical and Electronics Engineers, Inc., 2020)Path loss prediction is essential for network planning in any wireless communication system. For cellular networks, it is usually achieved through extensive received signal power measurements in the target area. When the ... -
Regression of large-scale path loss parameters using deep neural networks
(IEEE-Institute of Electrical and Electronics Engineers Inc., 2022)Path loss exponent and shadowing factor are among important wireless channel parameters. These parameters can be estimated using field measurements or ray-tracing simulations, which are costly and time-consuming. In this ... -
rs-fMRI analysis using spatio-temporal sparse convolutional neural networks
(Institute of Electrical and Electronics Engineers Inc., 2022)Neuropsychiatric diseases such as Autism Spectrum Disorder (ASD) and Schizophrenia cause various behavioral and communication dysfunctions in human life. Resting state functional magnetic resonance imaging (rs-fMRI) is ... -
Spectrum occupancy prediction exploiting time and frequency correlations through 2D-LSTM
(Institute of Electrical and Electronics Engineers Inc., 2020)The identification of spectrum opportunities is a pivotal requirement for efficient spectrum utilization in cognitive radio systems. Spectrum prediction offers a convenient means for revealing such opportunities based on ...