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Toplam kayıt 5, listelenen: 1-5
A Two-Phase Approach using Mask R-CNN and 3D U-Net for High-Accuracy Automatic Segmentation of Pancreas in CT Imaging
(Elsevier Ireland Ltd, 2021)
Background and objective: The size, shape, and position of the pancreas are affected by the patient characteristics such as age, sex, adiposity. Owing to more complex anatomical structures (size, shape, and position) of ...
Predicting Stock Prices Using Machine Learning Methods and Deep Learning Algorithms: The Sample of the Istanbul Stock Exchange
(Gazi Univ, 2021)
Stock market prediction in financial and commodity markets is a major challenge for speculators, investors, and companies but also profitable with an accurate prediction. Thus, obtaining accurate prediction results becomes ...
ReCRNet: a deep residual network for crack detection in historical buildings
(Springer Heidelberg, 2021)
In historical buildings, surface cracks are important indicators of potential structural damage. Natural disasters and indirect human factors, which are frequently encountered in recent periods, negatively affect historical ...
A study on effective data preprocessing and augmentation method in diabetic retinopathy classification using pre-trained deep learning approaches
(Springer, 2023)
High glucose levels in the blood not only damage different tissues and organs of the body, but also cause adverse effects on the eye. This condition is called diabetic retinopathy (DR). DR can cause blurred vision, darkening ...
Detection of forest fire using deep convolutional neural networks with transfer learning approach[Formula presented
(Elsevier Ltd, 2023)
Forest fires caused by natural causes such as climate change, temperature increase, lightning strikes, volcanic activity or human effects are among the world's most dangerous, deadly, and destructive disasters. Detection, ...