Bölüm "İstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü" Bildiri Koleksiyonu için listeleme
Toplam kayıt 7, listelenen: 1-7
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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, ... -
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 ... -
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 ... -
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 ... -
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) ... -
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 ...