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Toplam kayıt 18, listelenen: 1-10
Deep neural network approach to estimation of power production for an organic Rankine cycle system
(Springer, 2020)
In this study, the possibility of using Stepwise multilinear regression and deep learning models to estimate the behaviour of the organic Rankine cycle (ORC) has been investigated. It was found that a number of parameters ...
Prediction of Leakage from an Axial Piston Pump Slipper with Circular Dimples Using Deep Neural Networks
(Springer, 2020)
Oil leakage between the slipper and swash plate of an axial piston pump has a significant effect on the efficiency of the pump. Therefore, it is extremely important that any leakage can be predicted. This study investigates ...
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, ...
Plant leaf disease classification using EfficientNet deep learning model
(Elsevier, 2021)
Most plant diseases show visible symptoms, and the technique which is accepted today is that an experienced plant pathologist diagnoses the disease through optical observation of infected plant leaves. The fact that the ...
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 ...
Forecasting Models For Covid-19 Cases of Turkey Using Artificial Neural Networks and Deep Learning
(TMMOB Makina Mühendisleri Odası, 2020)
Governments face a dilemma between public health and the economy while making strategic decisions
on health during a pandemic outbreak. It is of great importance to forecast the number of cases in terms
of strategic ...
CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations
(Oxford Academic, 2021)
Systemic analysis of available large-scale biological/biomedical data is critical for studying biological mechanisms, and developing novel and effective treatment approaches against diseases. However, different layers 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, ...
Automated detection of Covid-19 disease using deep fused features from chest radiography images
(Elsevier, 2021)
The health systems of many countries are desperate in the face of Covid-19, which has become a pandemic worldwide and caused the death of hundreds of thousands of people. In order to keep Covid-19, which has a very high ...
Drug-resistant Staphylococcus aureus bacteria detection by combining surface-enhanced Raman spectroscopy (SERS) and deep learning techniques
(Nature Research, 2021)
Over the past year, the world's attention has focused on combating COVID-19 disease, but the other threat waiting at the door-antimicrobial resistance should not be forgotten. Although making the diagnosis rapidly and ...