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Toplam kayıt 7, listelenen: 1-7
An adaptive deep learning framework to classify unknown composite power quality event using known single power quality events
(Pergamon-Elsevier Science Ltd, 2021)
Distributed generation (DG) sources are preferred to meet today's energy needs effectively. The addition of many different types of renewable energy sources to the grid causes various problems in signal quality. Detection ...
A comprehensive survey of deep learning research on medical image analysis with focus on transfer learning
(Elsevier Science Inc, 2023)
This survey aims to identify commonly used methods, datasets, future trends, knowledge gaps, constraints, and limitations in the field to provide an overview of current solutions used in medical image analysis in parallel ...
A comparative study of vision transformers and convolutional neural networks: sugarcane leaf diseases identification
(Springer, 2023)
Diseases in agricultural products cause significant decrease on harvest efficiency and economic values of the products, early detection of diseases can prevent this loss. The development of artificial intelligence has ...
Application of Pre-Trained Deep Convolutional Neural Networks for Coffee Beans Species Detection
(Springer, 2022)
Coffee is an important export product of the tropical countries where it is grown. Therefore, the separation of coffee beans in the world in terms of the quality element and variety forgery is an important situation. ...
Dimension optimization of multi-band microstrip antennas using deep learning methods
(Pamukkale Univ, 2021)
The electromagnetic frequency spectrum is divided into different sub-frequency bands. These sub-frequency bands are allocated for different applications. In these days, devices operating in multiple sub-frequency bands ...
Parallel-stream fusion of scan-specific and scan-general priors for learning deep MRI reconstruction in low-data regimes
(Pergamon-Elsevier Science Ltd, 2023)
Magnetic resonance imaging (MRI) is an essential diagnostic tool that suffers from prolonged scan times. Reconstruction methods can alleviate this limitation by recovering clinically usable images from accelerated acquisitions. ...
Detection and classification of microcalcifications in mammograms images using difference filter and Yolov4 deep learning model
(Elsevier Sci Ltd, 2023)
In this study, we focus on increasing the visibility of microcalcifications (MCs) in mammogram images by means of the difference filter and classifying the visibility-increased MCs by using Yolov4 deep learning model. The ...