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Ilhan Aydin
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2020 – today
- 2024
- [c22]Musa Yenilmez, Ilhan Aydin:
A Federated Learning-Based Approach for Classification of Histopathology Images. ACIT 2024: 749-752 - 2023
- [j17]Mehmet Sevi, Ilhan Aydin:
Improving Unet segmentation performance using an ensemble model in images containing railway lines. Turkish J. Electr. Eng. Comput. Sci. 31(4): 739-750 (2023) - 2022
- [j16]Ilhan Aydin, Mehmet Sevi, Mehmet Umut Salur, Erhan Akin:
Defect classification of railway fasteners using image preprocessing and alightweight convolutional neural network. Turkish J. Electr. Eng. Comput. Sci. 30(3): 891-907 (2022) - [j15]Mehmet Umut Salur
, Ilhan Aydin
A soft voting ensemble learning-based approach for multimodal sentiment analysis. Neural Comput. Appl. 34(21): 18391-18406 (2022) - [c21]Gulsah Karaduman, Ilhan Aydin, Erhan Akin, Selçuk Özdemir:
Detection of the Steel Faults Based on Deep Learning. INISTA 2022: 1-2 - [c20]Ilhan Aydin, Selçuk Sinan Kirat
Detection of Rail Surface Defects with Two Deep Learning Methods: Comparative Analysis. SIU 2022: 1-4 - 2021
- [j14]Ilhan Aydin
Defect classification based on deep features for railway tracks in sustainable transportation. Appl. Soft Comput. 111: 107706 (2021) - [j13]Nashwan Adnan Othman
Challenges and Limitations in Human Action Recognition on Unmanned Aerial Vehicles: A Comprehensive Survey. Traitement du Signal 38(5): 1403-1411 (2021) - [c19]Mehmet Sevi
Detecting Flaws on Railways Using Semantic Segmentation. ICIT 2021: 179-183 - [c18]Emre Güçlü, Ilhan Aydin, Erhan Akin:
Fuzzy PID Based Autonomous UAV Design for Railway Tracking. ICIT 2021: 456-461 - [c17]Ahmet Aydin, Mehmet Umut Salur
Fine-Tuning Convolutional Neural Network Based Railway Damage Detection. EUROCON 2021: 216-221 - 2020
- [j12]Mehmet Umut Salur
A Novel Hybrid Deep Learning Model for Sentiment Classification. IEEE Access 8: 58080-58093 (2020) - [j11]Ilhan Aydin
A new method for time series classification using multi-dimensional phase space and a statistical control chart. Neural Comput. Appl. 32(11): 7439-7453 (2020) - [j10]Ilhan Aydin, Seyfullah Kaner:
A New Hybrid Diagnosis of Bearing Faults Based on Time-Frequency Images and Sparse Representation. Traitement du Signal 37(6): 907-918 (2020)
2010 – 2019
- 2018
- [j9]Ilhan Aydin, Mehmet Karaköse
A new fault diagnosis approach for induction motor using negative selection algorithm and its real-time implementation on FPGA. J. Intell. Fuzzy Syst. 34(1): 689-701 (2018) - [j8]Ebru Karakose, Muhsin Tunay Gençoglu, Mehmet Karaköse
A new arc detection method based on fuzzy logic using S-transform for pantograph-catenary systems. J. Intell. Manuf. 29(4): 839-856 (2018) - [c16]Mehmet Umut Salur
Sentiment classification based on deep learning. SIU 2018: 1-4 - 2017
- [j7]Ebru Karakose, Muhsin Tunay Gençoglu, Mehmet Karaköse
A New Experimental Approach Using Image Processing-Based Tracking for an Efficient Fault Diagnosis in Pantograph-Catenary Systems. IEEE Trans. Ind. Informatics 13(2): 635-643 (2017) - 2016
- [c15]Canan Tastimur, Mehmet Karaköse
Rail defect detection with real time image processing technique. INDIN 2016: 411-415 - [c14]Ilhan Aydin, Mehmet Karaköse
A new real-time fuzzy logic based diagnosis of stator faults for inverter-fed induction motor under low speeds. INDIN 2016: 446-451 - [c13]Mehmet Karaköse
Real-time condition monitoring approach of pantograph-catenary system using FPGA. INDIN 2016: 481-486 - [c12]Yunus Santur, Mehmet Karaköse
IMU based adaptive blur removal approach using image processing for railway inspection. IWSSIP 2016: 1-4 - 2015
- [j6]Ilhan Aydin, Mehmet Karaköse
Anomaly detection using a modified kernel-based tracking in the pantograph-catenary system. Expert Syst. Appl. 42(2): 938-948 (2015) - [j5]Ilhan Aydin, Mehmet Karaköse
Combined intelligent methods based on wireless sensor networks for condition monitoring and fault diagnosis. J. Intell. Manuf. 26(4): 717-729 (2015) - [c11]Orhan Yaman
Image processing based fault detection approach for rail surface. SIU 2015: 1118-1121 - [c10]Canan Tastimur, Erhan Akin
Detection of rail faults using morphological feature extraction based image processing. SIU 2015: 1244-1247 - 2014
- [c9]Ilhan Aydin, Orhan Yaman
Particle swarm based arc detection on time series in pantograph-catenary system. INISTA 2014: 344-349 - [c8]Ilhan Aydin, Mehmet Karaköse, Erhan Akin:
Monitoring of pantograph-catenary interaction by using particle swarm based contact wire tracking. IWSSIP 2014: 23-26 - [c7]Orhan Yaman
Detection of pantograph geometric model based on fuzzy logic and image processing. SIU 2014: 686-689 - [c6]Orhan Yaman
Image processing and model based arc detection in pantograph catenary systems. SIU 2014: 1934-1937 - 2013
- [c5]Ilhan Aydin, Mehmet Karaköse
A new approach based on boundary analysis of reconstructed phase space for fault diagnosis. ASCC 2013: 1-6 - [c4]Orhan Yaman
Wireless sensor network based fault diagnosis approaches. SIU 2013: 1-4 - [c3]Ilhan Aydin, Mehmet Karaköse
A Robust Anomaly Detection in Pantograph-Catenary System Based on Mean-Shift Tracking and Foreground Detection. SMC 2013: 4444-4449 - 2012
- [j4]Ilhan Aydin, Mehmet Karaköse
An adaptive artificial immune system for fault classification. J. Intell. Manuf. 23(5): 1489-1499 (2012) - 2011
- [b1]Ilhan Aydin:
Gerçek zamanlı durum izleme ve arıza teşhisi için bağışık akıllı hesaplama tekniklerinin geliştirilmesi (Development of immune intelligent computing techniques for real-time condition monitoring and fault diagnosis). Fırat University, Turkey, 2011 - [j3]Ilhan Aydin, Mehmet Karaköse
A multi-objective artificial immune algorithm for parameter optimization in support vector machine. Appl. Soft Comput. 11(1): 120-129 (2011) - 2010
- [j2]Ilhan Aydin, Mehmet Karaköse
Artificial immune classifier with swarm learning. Eng. Appl. Artif. Intell. 23(8): 1291-1302 (2010) - [j1]Ilhan Aydin, Mehmet Karaköse
Chaotic-based hybrid negative selection algorithm and its applications in fault and anomaly detection. Expert Syst. Appl. 37(7): 5285-5294 (2010) - [c2]Ilhan Aydin, Mehmet Karaköse
Generation of classification rules using artificial immune system for fault diagnosis. SMC 2010: 343-349 - [c1]Ilhan Aydin, Mehmet Karaköse
FPGA based real time fuzzy fault detection algorithm. SoCPaR 2010: 389-394
Coauthor Index
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