Zafer Cömert
Orcid: 0000-0001-5256-7648Affiliations:
- Bitlis Eren University, Department of Computer Engineering, Turkey
According to our database1,
Zafer Cömert
authored at least 29 papers
between 2015 and 2022.
Collaborative distances:
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Bibliography
2022
Neighbourhood component analysis and deep feature-based diagnosis model for middle ear otoscope images.
Neural Comput. Appl., 2022
2021
Otitis media detection using tympanic membrane images with a novel multi-class machine learning algorithm.
PeerJ Comput. Sci., 2021
A systematic review of automated pre-processing, feature extraction and classification of cardiotocography.
PeerJ Comput. Sci., 2021
Detection of weather images by using spiking neural networks of deep learning models.
Neural Comput. Appl., 2021
Enhancing of dataset using DeepDream, fuzzy color image enhancement and hypercolumn techniques to detection of the Alzheimer's disease stages by deep learning model.
Neural Comput. Appl., 2021
Tumor type detection in brain MR images of the deep model developed using hypercolumn technique, attention modules, and residual blocks.
Medical Biol. Eng. Comput., 2021
Efficient COVID-19 Segmentation from CT Slices Exploiting Semantic Segmentation with Integrated Attention Mechanism.
J. Digit. Imaging, 2021
2020
Corrigendum to "Classification of brain MRI using hyper column technique with convolutional neural network and feature selection method" Expert Systems with Applications 149 (2020) 1-8 /113274.
Expert Syst. Appl., 2020
Classification of brain MRI using hyper column technique with convolutional neural network and feature selection method.
Expert Syst. Appl., 2020
COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches.
Comput. Biol. Medicine, 2020
Convolutional neural network approach for automatic tympanic membrane detection and classification.
Biomed. Signal Process. Control., 2020
Classification of white blood cells using deep features obtained from Convolutional Neural Network models based on the combination of feature selection methods.
Appl. Soft Comput., 2020
A Novel Medical Diagnosis model for COVID-19 infection detection based on Deep Features and Bayesian Optimization.
Appl. Soft Comput., 2020
Automatic determination of digital modulation types with different noises using Convolutional Neural Network based on time-frequency information.
Appl. Soft Comput., 2020
2019
Prediction of intrapartum fetal hypoxia considering feature selection algorithms and machine learning models.
Health Inf. Sci. Syst., 2019
Identification of haploid and diploid maize seeds using convolutional neural networks and a transfer learning approach.
Comput. Electron. Agric., 2019
Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images.
Appl. Soft Comput., 2019
2018
Prognostic model based on image-based time-frequency features and genetic algorithm for fetal hypoxia assessment.
Comput. Biol. Medicine, 2018
Biomed. Signal Process. Control., 2018
Intelligent system based on Genetic Algorithm and support vector machine for detection of myocardial infarction from ECG signals.
Proceedings of the 26th Signal Processing and Communications Applications Conference, 2018
Proceedings of the 26th Signal Processing and Communications Applications Conference, 2018
Performance evaluation of Empirical Mode Decomposition and Discrete Wavelet Transform for computerized hypoxia detection and prediction.
Proceedings of the 26th Signal Processing and Communications Applications Conference, 2018
The influences of different window functions and lengths on image-based time-frequency features of fetal heart rate signals.
Proceedings of the 26th Signal Processing and Communications Applications Conference, 2018
Fetal Hypoxia Detection Based on Deep Convolutional Neural Network with Transfer Learning Approach.
Proceedings of the Software Engineering and Algorithms in Intelligent Systems, 2018
2017
Kardiyotokografi işaretlerinin analizi ve makine öğrenmesi teknikleri ile sınıflandırılması (Analysis of cardiotocography signals and classifying with machine learning techniques)
PhD thesis, 2017
Cardiotocography analysis based on segmentation-based fractal texture decomposition and extreme learning machine.
Proceedings of the 25th Signal Processing and Communications Applications Conference, 2017
Proceedings of the 25th Signal Processing and Communications Applications Conference, 2017
2016
Cardiotocography signals with artificial neural network and extreme learning machine.
Proceedings of the 24th Signal Processing and Communication Application Conference, 2016
2015
Proceedings of the 2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015