Derin öğrenme modelleri ve uygulama alanlarına ilişkin bir derleme
F Doğan, İ Türkoğlu - Dicle Üniversitesi Mühendislik Fakültesi …, 2019 - dergipark.org.tr
Derin öğrenme makine öğreniminin bir koludur. Makine öğreniminin başlarından günümüze
kadar geçen süreçte yapay zekaya olan ilgi giderek artmış ve günümüzde en çok kullanılan …
kadar geçen süreçte yapay zekaya olan ilgi giderek artmış ve günümüzde en çok kullanılan …
CNN hyper-parameter optimization for environmental sound classification
Ö İnik - Applied Acoustics, 2023 - Elsevier
Environmental sounds are being used widely in our lives. It is especially used in tasks such
as managing smart cities, location determination, surveillance systems, machine hearing …
as managing smart cities, location determination, surveillance systems, machine hearing …
Konvolüsyonel sinir ağlarında hiper-parametre optimizasyonu yöntemlerinin incelenmesi
Purpose: In this study, meta-heuristic methods that have been used to optimize
convolutional neural networks are investigated. A performance comparison of these …
convolutional neural networks are investigated. A performance comparison of these …
Multi-model CNN fusion for sperm morphology analysis
Infertility is a common disorder affecting 20% of couples worldwide. Furthermore, 40% of all
cases are related to male infertility. The first step in the determination of male infertility is …
cases are related to male infertility. The first step in the determination of male infertility is …
Detection of pulpal calcifications on bite-wing radiographs using deep learning
Objectives Pulpal calcifications are discrete hard calcified masses of varying sizes in the
dental pulp cavity. This study is aimed at measuring the performance of the YOLOv4 deep …
dental pulp cavity. This study is aimed at measuring the performance of the YOLOv4 deep …
An eye state recognition system using transfer learning: AlexNet-based deep convolutional neural network
For eye state recognition (closed or open), a mechanism based on deep convolutional
neural network (DCNN) using the Zhejiang University (ZJU) and Closed Eyes in the Wild …
neural network (DCNN) using the Zhejiang University (ZJU) and Closed Eyes in the Wild …
MFIF-DWT-CNN: Multi-focus ımage fusion based on discrete wavelet transform with deep convolutional neural network
A new fusion method based on Multi-Focus Image Fusion Based on Discrete Wavelet
Transform with Deep Convolutional Neural Network (MFIF-DWT-CNN) is presented to …
Transform with Deep Convolutional Neural Network (MFIF-DWT-CNN) is presented to …
Transfer learning to detect neonatal seizure from electroencephalography signals
A Caliskan, S Rencuzogullari - Neural Computing and Applications, 2021 - Springer
This paper offers a solution to the problem of detecting neonatal seizures via a transfer
learning technique that judiciously reconstructs pre-trained deep convolution neural …
learning technique that judiciously reconstructs pre-trained deep convolution neural …
Demagnetization fault detection of permanent magnet synchronous motor with convolutional neural network
M Eker, B Gündogan - Electrical Engineering, 2023 - Springer
In this study, the convolutional neural network (CNN) architecture of deep learning was used
to diagnose a demagnetization fault that occurred in permanent magnet synchronous motors …
to diagnose a demagnetization fault that occurred in permanent magnet synchronous motors …
Recognizing students and detecting student engagement with real-time image processing
With COVID-19, formal education was interrupted in all countries and the importance of
distance learning has increased. It is possible to teach any lesson with various …
distance learning has increased. It is possible to teach any lesson with various …