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ORCIDSerhat Kiliçarslan
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2020 – today
- 2024
[j15]Serhat Kiliçarslan
, Emrah Dönmez:
Improved multi-layer hybrid adaptive particle swarm optimization based artificial bee colony for optimizing feature selection and classification of microarray data. Multim. Tools Appl. 83(26): 67259-67281 (2024)- [j14]Serhat Kiliçarslan, Mete Celik:
Parametric RSigELU: a new trainable activation function for deep learning. Neural Comput. Appl. 36(13): 7595-7607 (2024) - [j13]Cemil Közkurt, Aykut Diker, Abdullah Elen, Serhat Kiliçarslan, Emrah Dönmez, Fahrettin Burak Demir:
Trish: an efficient activation function for CNN models and analysis of its effectiveness with optimizers in diagnosing glaucoma. J. Supercomput. 80(11): 15485-15516 (2024) - 2023
- [j12]Serhat Kiliçarslan, Cemil Közkurt, Selçuk Bas, Abdullah Elen:
Detection and classification of pneumonia using novel Superior Exponential (SupEx) activation function in convolutional neural networks. Expert Syst. Appl. 217: 119503 (2023) - [j11]Dilek Sabanci, Serhat Kiliçarslan, Kemal Adem:
An application on forecasting for stock market prices: hybrid of some metaheuristic algorithms with multivariate adaptive regression splines. Int. J. Intell. Comput. Cybern. 16(4): 847-866 (2023) - [j10]Serhat Kiliçarslan:
PSO + GWO: a hybrid particle swarm optimization and Grey Wolf optimization based Algorithm for fine-tuning hyper-parameters of convolutional neural networks for Cardiovascular Disease Detection. J. Ambient Intell. Humaniz. Comput. 14(1): 87-97 (2023) - [j9]Emrah Dönmez, Serhat Kiliçarslan, Cemil Közkurt, Aykut Diker, Fahrettin Burak Demir, Abdullah Elen:
Identification of haploid and diploid maize seeds using hybrid transformer model. Multim. Syst. 29(6): 3833-3845 (2023) - [j8]Serhat Kiliçarslan:
A novel nonlinear hybrid HardSReLUE activation function in transfer learning architectures for hemorrhage classification. Multim. Tools Appl. 82(4): 6345-6365 (2023) - [j7]Shigao Huang, Ibrahim Arpaci, Mostafa Al-Emran, Serhat Kiliçarslan, Mohammed A. Al-Sharafi:
A comparative analysis of classical machine learning and deep learning techniques for predicting lung cancer survivability. Multim. Tools Appl. 82(22): 34183-34198 (2023) - [j6]Ishak Paçal, Serhat Kiliçarslan:
Deep learning-based approaches for robust classification of cervical cancer. Neural Comput. Appl. 35(25): 18813-18828 (2023) - [j5]Cemil Közkurt, Serhat Kiliçarslan, Selçuk Bas, Abdullah Elen:
αSechSig and αTanhSig: two novel non-monotonic activation functions. Soft Comput. 27(24): 18451-18467 (2023) - 2022
- [j4]Serhat Kiliçarslan, Mete Celik:
KAF + RSigELU: a nonlinear and kernel-based activation function for deep neural networks. Neural Comput. Appl. 34(16): 13909-13923 (2022) - 2021
- [b1]Serhat Kiliçarslan:
Derin öğrenme yöntemleri için doğrusal olmayan aktivasyon fonksiyonlarının geliştirilmesi (Development of nonlinear activation functions for deep learning methods). Erciyes University, Turkey, 2021 - [j3]Serhat Kiliçarslan, Mete Celik, Safak Sahin:
Hybrid models based on genetic algorithm and deep learning algorithms for nutritional Anemia disease classification. Biomed. Signal Process. Control. 63: 102231 (2021) - [j2]Serhat Kiliçarslan, Mete Celik:
RSigELU: A nonlinear activation function for deep neural networks. Expert Syst. Appl. 174: 114805 (2021)
2010 – 2019
- 2019
- [j1]Kemal Adem, Serhat Kiliçarslan, Onur Cömert:
Classification and diagnosis of cervical cancer with softmax classification with stacked autoencoder. Expert Syst. Appl. 115: 557-564 (2019)
Coauthor Index
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