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Ishak Paçal
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2020 – today
- 2024
- [j15]Rodrigo Fernandes
, Alexandre Pessoa, Marta Salgado
Enhancing Image Annotation With Object Tracking and Image Retrieval: A Systematic Review. IEEE Access 12: 79428-79444 (2024) - [j14]Ishak Paçal, Omer Celik, Bilal Bayram, António Cunha
Enhancing EfficientNetv2 with global and efficient channel attention mechanisms for accurate MRI-Based brain tumor classification. Clust. Comput. 27(8): 11187-11212 (2024) - [j13]Ishak Paçal
Enhancing crop productivity and sustainability through disease identification in maize leaves: Exploiting a large dataset with an advanced vision transformer model. Expert Syst. Appl. 238(Part E): 122099 (2024) - [j12]Ishak Paçal
MaxCerVixT: A novel lightweight vision transformer-based Approach for precise cervical cancer detection. Knowl. Based Syst. 289: 111482 (2024) - [j11]Ishak Paçal
A novel Swin transformer approach utilizing residual multi-layer perceptron for diagnosing brain tumors in MRI images. Int. J. Mach. Learn. Cybern. 15(9): 3579-3597 (2024) - [j10]Mohammed Lubbad
Machine learning applications in detection and diagnosis of urology cancers: a systematic literature review. Neural Comput. Appl. 36(12): 6355-6379 (2024) - [j9]Melek Alaftekin, Ishak Paçal
Real-time sign language recognition based on YOLO algorithm. Neural Comput. Appl. 36(14): 7609-7624 (2024) - [j8]Gültekin Isik
Few-shot classification of ultrasound breast cancer images using meta-learning algorithms. Neural Comput. Appl. 36(20): 12047-12059 (2024) - 2023
- [j7]Ahmet Karaman, Dervis Karaboga, Ishak Paçal
Hyper-parameter optimization of deep learning architectures using artificial bee colony (ABC) algorithm for high performance real-time automatic colorectal cancer (CRC) polyp detection. Appl. Intell. 53(12): 15603-15620 (2023) - [j6]Damla Coskun, Dervis Karaboga, Alper Bastürk, Bahriye Akay
A comparative study of YOLO models and a transformer-based YOLOv5 model for mass detection in mammograms. Turkish J. Electr. Eng. Comput. Sci. 31(7): 1294-1313 (2023) - [j5]Ahmet Karaman, Ishak Paçal
Robust real-time polyp detection system design based on YOLO algorithms by optimizing activation functions and hyper-parameters with artificial bee colony (ABC). Expert Syst. Appl. 221: 119741 (2023) - [j4]Ishak Paçal
Deep learning-based approaches for robust classification of cervical cancer. Neural Comput. Appl. 35(25): 18813-18828 (2023) - [c2]Rodrigo Fernandes, Alexandre Pessoa, José Nogueira, Anselmo Cardoso de Paiva, Ishak Paçal, Marta Salgado, António Cunha
Evaluation of Deep Learning Models in Search by Example using Capsule Endoscopy Images. CENTERIS/ProjMAN/HCist 2023: 1653-1661 - [c1]Rodrigo Fernandes, Alexandre Pessoa, José Nogueira, Anselmo Cardoso de Paiva, Ishak Paçal, Marta Salgado, António Cunha:
Evaluation of Deep Learning Models in Search by Example using Capsule Endoscopy Images. CENTERIS/ProjMAN/HCist 2023: 2065-2073 - 2022
- [b1]Ishak Paçal:
Derin öğrenme tabanlı gerçek zamanlı polip tespit yöntemlerinin geliştirilmesi ve incelenmesi (Development and investigation of deep learning based real-time polyp detection methods). Erciyes University, Turkey, 2022 - [j3]Ishak Paçal
An efficient real-time colonic polyp detection with YOLO algorithms trained by using negative samples and large datasets. Comput. Biol. Medicine 141: 105031 (2022) - 2021
- [j2]Ishak Paçal
A robust real-time deep learning based automatic polyp detection system. Comput. Biol. Medicine 134: 104519 (2021) - 2020
- [j1]Ishak Paçal
A comprehensive review of deep learning in colon cancer. Comput. Biol. Medicine 126: 104003 (2020)
Coauthor Index
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last updated on 2024-12-10 20:49 CET by the dblp team
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