Browsing Makale Koleksiyonu by Title
Now showing items 1-20 of 59
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Analysis of functional brain connections for positive-negative emotions using phase locking value
(Springer, 2017)In this study, we investigate the brain networks during positive and negative emotions for different types of stimulus (audio only, video only and audio + video) in , and bands in terms of phase locking value, a nonlinear ... -
Approximate analytical solutions of a class of non-linear fractional boundary value problems with conformable derivative
(Serbian Society of Heat Transfer Engineers, 2021)In this paper, it is presented that an approximate solution of a class of non-linear differential equations with conformable derivative under boundary conditions by using sinc-Galerkin method that is not used to approximately ... -
Approximate solutions of Volterra-Fredholm integro-differential equations of fractional order
(Tbilisi Centre For Mathematical Sciences, 2017)In this study, sine-collocation Method is introduced for solving Volterra-Fredholm integro-differential equations of fractional order. Fractional derivative is described in the Caputo sense, Obtained results are given to ... -
Breast cancer diagnosis using deep belief networks on ROI images
(Pamukkale Üniversitesi, 2022)Hand-crafted features are efficient methods for image processing, recognition, and computer vision. However, the advancements in data size and image resolution lead to inconvenience in feature extraction. Moreover, they ... -
Bul-Tak Oyuncağı Şekillerinin Klasik Görüntü İşleme ve Derin Öğrenme Yöntemleri ile Tespiti
(Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 2021)Bilgisayar görme algoritmaları, teknolojinin ilerlemesiyle daha kullanılır hale gelmektedir. Klasik yöntemler olan görüntü işleme ve makine öğrenmesi algoritmaları ile yapılan bilgisayarlı görü uygulamaları halen kullanılsa ... -
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
(Bmc, 2019)Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the ... -
Chronic obstructive pulmonary disease severity analysis using deep learning on multi-channel lung sounds
(Türkiye Klinikleri, 2020)Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases which cannot be treated but can be kept under control in certain stages. COPD has five severities, including at-risk, mild, moderate, severe, ... -
A collocation method for solving boundary value problems of fractional order
(Sakarya Üniversitesi, 2018)In this work, the Sinc-Collocation Method (SCM) is used to find the approximate solutions of the secondorder fractional boundary value problems based on the conformable fractional derivative. For this purpose, a theorem ... -
Current Operational Amplifier Based Voltage-Mode MOS-C All-Pass Filter and Its Application
(Gazi Üniversitesi, 2020)In this work, a novel first order voltage-mode all-pass filter employing single active element named current operational amplifier (COA), two resistors, one capacitor and it's application as sinusoidal oscillator is ... -
Deep Convolutional Generalized Classifier Neural Network
(Springer, 2020)Up to date technological implementations of deep convolutional neural networks are at the forefront of many issues, such as autonomous device control, effective image and pattern recognition solutions. Deep neural networks ... -
Deep Learning on Computerized Analysis of Chronic Obstructive Pulmonary Disease
(Institute of Electrical and Electronics Engineers Inc., 2020)Goal: Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases in the world. Because COPD is an incurable disease and requires considerable time to be diagnosed even by an experienced specialist, it ... -
Deep learning with 3D-second order difference plot on respiratory sounds
(Elsevier, 2018)The second order difference plot (SODP) is a nonlinear signal analysis method that visualizes two consecutive data points for many types of biomedical signals. The proposed method is based on analysing quantization of ... -
Deep Learning with ConvNet Predicts Imagery Tasks Through EEG
(Springer, 2021)Deep learning with convolutional neural networks (ConvNets) has dramatically improved the learning capabilities of computer vision applications just through considering raw data without any prior feature extraction. Nowadays, ... -
Deep Learning-based Mammogram Classification for Breast Cancer
(International Journal of Intelligent Systems and Applications in Engineering, 2020)Deep Learning (DL) is a rising field of researches in last decade by exposing a hybrid analysis procedure including advanced level image processing and many efficient supervised classifiers. Robustness of the DL algorithms ... -
DeepGraphNet: Grafiklerin Sınıflandırılmasında Derin Öğrenme Modelleri
(Avrupa Bilim ve Teknoloji Dergisi, 2019)Grafik sınıflandırma modeli henüz yeni bir araştırma alanı olarak ön plana çıkan bir görüntü işleme yaklaşımıdır. Özellikle verilerin görselleştirilmesi ve kolay okunabilirliğini sağlamak için tercih edilen grafikler, ... -
DeepOCT: An explainable deep learning architecture to analyze macular edema on OCT images
(Elsevier, 2022)Macular edema (ME) is one of the most common retinal diseases that occur as a result of the detachment of the retinal layers on the macula. This study provides computer-aided identification of ME for even small pathologies ... -
DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks
(Nature Publishing Group, 2019)Automated protein function prediction is critical for the annotation of uncharacterized protein sequences, where accurate prediction methods are still required. Recently, deep learning based methods have outperformed ... -
DEEPScreen: high performance drug-target interaction prediction with convolutional neural networks using 2-D structural compound representations
(Royal Soc Chemistry, 2020)The identification of physical interactions between drug candidate compounds and target biomolecules is an important process in drug discovery. Since conventional screening procedures are expensive and time consuming, ... -
DiCDU: distributed clustering with decreased uncovered nodes for WSNs
(Institution of Engineering and Technology (IET), 2020)This study proposes a distributed cluster-based routing algorithm, distributed clustering with decreased uncovered nodes (DiCDU), alleviating the uncovered node problem occurring after the election of cluster heads. For ... -
Differential convolutional neural network
(Elsevier, 2019)Convolutional neural networks with strong representation ability of deep structures have ever increasing popularity in many research areas. The main difference of Convolutional Neural Networks with respect to existing ...
