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Toplam kayıt 13, listelenen: 1-10
A Multistage Deep Learning Algorithm for Detecting Arrhythmia
(Institute of Electrical and Electronics Engineers, 2018)
Deep Belief Networks (DBN) is a deep learning algorithm that has both greedy layer-wise unsupervised and supervised training. Arrhythmia is a cardiac irregularity caused by a problem of the heart. In this study, a multi-stage ...
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 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 ...
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, ...
SecureDeepNet-IoT: A deep learning application for invasion detection in industrial Internet of Things sensing systems
(Wiley, 2021)
Deep learning (DL) is a special field of artificial intelligence that has increased its use in various fields and has proved its effectiveness in classification. The feasibility of using many hidden layers and many neurons ...
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-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 ...
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, ...
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 ...
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, ...