Başlık için Bilgisayar Mühendisliği listeleme
Toplam kayıt 90, listelenen: 16-35
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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 ... -
A deep learning architecture for identification of breast cancer on mammography by learning various representations of cancerous mass
(Springer, 2021)Deep Learning (DL) is a high capable machine learning algorithm with the detailed analysis abilities on images. Although DL models achieve very high classification performances, the applications are trending on using and ... -
Deep Learning for COPD Analysis Using Lung Sounds
(Baku State University, 2018)In this study, Hilbert-Huang Transform (HHT) was applied to the lung sounds from RespiratoryDatabase@TR and the statistical features were calculated from the different modulations of the HHT. The statistical features were ... -
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 ... -
Dynamic coefficient-based cluster head election in wireless sensor networks
(Pamukkale Üniversitesi, 2020)Owing to the fact that the selection of cluster heads has a significant effect on the lifetime of the network, many researches have proposed various cluster head election methodologies for cluster-based WSNs. Although ... -
ECG based human identification using Second Order Difference Plots
(Elsevier, 2019)Background and objective: ECG is one of the biometric signals that has been studied in peer-reviewed over past years. The developments on the signal analysis methods show that the studies on the ECG would continue unabatedly. ... -
ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature
(BMC, 2018)Background: The automated prediction of the enzymatic functions of uncharacterized proteins is a crucial topic in bioinformatics. Although several methods and tools have been proposed to classify enzymes, most of these ... -
The Effect of Auscultation Areas on Nonlinear Classifiers in Computerized Analysis of Chronic Obstructive Pulmonary Disease
(Springer, 2021)Today, with the rapid development of technology, various methods are being developed for computer assisted diagnostic systems. Computer assisted diagnostic systems allow an objective assessment and help physicians to ... -
An efficient scheme for solving a system of fractional differential equations with boundary conditions
(Springer International Publishing, 2017)In this study, the sinc collocation method is used to find an approximate solution of a system of differential equations of fractional order described in the Caputo sense. Some theorems are presented to prove the applicability ... -
Estimation of daily global solar radiation using deep learning model
(Elsevier, 2018)Solar radiation (SR) is an important data for various applications such as climate, energy and engineering. Because of this, determination and estimation of temporal and spatial variability of SR has critical importance ... -
Eşgüdümlü Bileşenler ile Birleştirme Yaklaşımı
(CEUR-WS, 2017)Bu çalışmada bileşen yönelimli sistem geliştirme yaklaşımlarında süreç modeli kullanımını desteklemek üzere farklı kabiliyetler gerektiren bileşen yapıları önerilmektedir. Bu yapılar ile merkezi bir süreç denetimi sağlamak ...