Bilgisayar Teknolojileri Bölümü
Recent Submissions
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Palmprint recognition system based on deep region of interest features with the aid of hybrid approach
(SpringerLink, 2023)Palmprint recognition system is a biometric technology, which is promising to have a high precision. This system has started to attract the attention of researchers, especially with the emergence of deep learning techniques ... -
Identification of cotton and corn plant areas by employing deep transformer encoder approach and different time series satellite images: A case study in Diyarbakir, Turkey
(ScienceDirect, 2023)It is very important to determine the crops in the agricultural field in a short time and accurately. Thanks to the satellite images obtained from remote sensing sensors, information can be obtained on many subjects such ... -
How advantageous is it to use computed tomography image-based artificial intelligence modelling in the differential diagnosis of chronic otitis media with and without cholesteatoma?
(European Review for Medical and Pharmacological Sciences, 2023)Abstract. – OBJECTIVE: Cholesteatoma (CHO) developing secondary to chronic otitis media (COM) can spread rapidly and cause important health problems such as hearing loss. Therefore, the presence of CHO should be diagnosed ... -
Performance Improvement of Genetic Algorithm Based Exam Seating Solution by Parameter Optimization
(Journal of Innovative Science and Engineering (JISE), 2022)Exam seat allocation has become a complex problem, with an increasing number of students, subjects, exams, departments, and rooms in higher education institutions. The requirements and constraints of this problem demonstrate ... -
Automatic detection of brain tumors with the aid of ensemble deep learning architectures and class activation map indicators by employing magnetic resonance images
(ScienceDirect, 2022)Today, as in every life-threatening disease, early diagnosis of brain tumors plays a life-saving role. The brain tumor is formed by the transformation of brain cells from their normal structures into abnormal cell structures. ... -
A comprehensive review on detection of cyber-attacks: Data sets, methods, challenges, and future research directions
(ScienceDirect, 2022)Rapid developments in network technologies and the amount and scope of data transferred on networks are increasing day by day. Depending on this situation, the density and complexity of cyber threats and attacks are also ... -
A Class Activation Map-Based Interpretable Transfer Learning Model for Automated Detection of ADHD from fMRI Data
(Sage Journals, 2022)Automatic detection of Attention Deficit Hyperactivity Disorder (ADHD) based on the functional Magnetic Resonance Imaging (fMRI) through Deep Learning (DL) is becoming a quite useful methodology due to the curse of-dimensionality ... -
FPGA simulation of chaotic tent map-based S-Box design
(Wiley Online Library, 2022)The chaotic system has a characteristically random behavior by nature, and these systems have their own characteristics in a completely deterministic structure. This feature of a chaotic system makes it difficult to ... -
Balina Optimizasyon Algoritması Kullanılarak Türkiye’nin Uzun Vadeli Enerji Tüketimi Tahmini
(IEEE Xplore, 2021)Enerji, ülkelerin sürdürülebilir kalkınmaları için en önemli konu başlıklarından biridir. Kullanılan enerjinin tükenebilir olması, birçok enerji kaynağını ithal ediyor olması ve çevresel faktörlerden dolayı Türkiye için ... -
Employing deep learning architectures for image-based automatic cataract diagnosis
(TÜBİTAK, 2021)Various eye diseases affect the quality of human life severely and ultimately may result in complete vision loss. Ocular diseases manifest themselves through mostly visual indicators in the early or mature stages of the ... -
Classification of Epilepsy Types from Electroencephalogram Time Series Using Continuous Wavelet Transform Scalogram-Based Convolutional Neural Network
(ASTM International, 2020)During the supervisory activities of the brain, the electrical activities of nerve cell clusters produce oscillations. These complex biopotential oscillations are called electroencephalogram (EEG) signals. Certain diseases, ... -
Classification of electroencephalogram records related to cursor movements with a hybrid method based on deep learning
(Wiley Online Library, 2021)In brain computer interface (BCI), many transformation methods are used whenprocessing electroencephalogram (EEG) signals. Thus, the EEG can be represen-ted in different domains. However, designing an EEG-based BCI system ... -
The convolutional neural network approach from electroencephalogram signals in emotional detection
(Concurrency Computation, 2021)Although brain-computer interfaces (BCI) progress rapidly, the desired success has not been achieved yet. One of these BCI is to detect emotional states in humans. An emotional state is a brain activity consisting of ... -
Epileptik EEG Sinyallerinin Sınıflandırılması için Bir Boyutlu Medyan Yerel İkili Örüntü Temelli Öznitelik Çıkarımı
(2017)Elektroansefalogram (EEG), epilepsi tespitinde yaygın olarak kullanılan önemli bir veri kaynağıdır. Bu çalışmada da Bonn Üniversitesi Epileptoloji bölümü veritabanından alınan ve A, B, C, D, E olmak üzere 5 işaret grubundan ... -
Epilepsy Detection by Using Scalogram Based Convolutional Neural Network from EEG Signals
(MDPI, 2019)The studies implemented with Electroencephalogram (EEG) signals are progressing very rapidly and brain computer interfaces (BCI) and disease determinations are carried out at certain success rates thanks to new methods ...
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