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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 ...
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, ...
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 ...