Ishak Paçal

According to our database, Ishak Paçal authored at least 26 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2025

Efficient and autonomous detection of olive leaf diseases using AI-enhanced MetaFormer.

Ishak Paçal, Serhat Kiliçarslan, Burhanettin Ozdemir, Muhammet Deveci, Seifedine Kadry

Artif. Intell. Rev., October, 2025

Utilizing convolutional neural networks and vision transformers for precise corn leaf disease identification.

Ishak Paçal, Gültekin Isik

Neural Comput. Appl., February, 2025

Hybrid deep learning model for automated colorectal cancer detection using local and global feature extraction.

Ishak Paçal, Omneya Attallah

Knowl. Based Syst., 2025

A novel hybrid ConvNeXt-based approach for enhanced skin lesion classification.

Ibrahim Aruk, Ishak Paçal, Ahmet Nusret Toprak

Expert Syst. Appl., 2025

A novel CNN-ViT-based deep learning model for early skin cancer diagnosis.

Ishak Paçal, Burhanettin Ozdemir, Javanshir Zeynalov, Huseyn Gasimov, Nurettin Pacal

Biomed. Signal Process. Control., 2025

InceptionNeXt-Transformer: A novel multi-scale deep feature learning architecture for multimodal breast cancer diagnosis.

Ishak Paçal, Omneya Attallah

Biomed. Signal Process. Control., 2025

Attention Enhanced InceptionNeXt-Based Hybrid Deep Learning Model for Lung Cancer Detection.

Burhanettin Ozdemir, Emrah Aslan, Ishak Paçal

IEEE Access, 2025

2024

Enhancing EfficientNetv2 with global and efficient channel attention mechanisms for accurate MRI-Based brain tumor classification.

Ishak Paçal, Omer Celik, Bilal Bayram, António Cunha

Clust. Comput., November, 2024

A systematic review of deep learning techniques for plant diseases.

Ishak Paçal, Ismail Kunduracioglu, Mehmet Hakki Alma, Muhammet Deveci, Seifedine Nimer Kadry, Jan Nedoma, Vlastimil Slany, Radek Martinek

Artif. Intell. Rev., November, 2024

A novel Swin transformer approach utilizing residual multi-layer perceptron for diagnosing brain tumors in MRI images.

Ishak Paçal

Int. J. Mach. Learn. Cybern., September, 2024

Few-shot classification of ultrasound breast cancer images using meta-learning algorithms.

Gültekin Isik, Ishak Paçal

Neural Comput. Appl., July, 2024

Real-time sign language recognition based on YOLO algorithm.

Melek Alaftekin, Ishak Paçal, Kenan Cicek

Neural Comput. Appl., May, 2024

Machine learning applications in detection and diagnosis of urology cancers: a systematic literature review.

Mohammed Lubbad, Dervis Karaboga, Alper Bastürk, Bahriye Akay, Özkan U. Nalbantoglu, Ishak Paçal

Neural Comput. Appl., April, 2024

Enhancing crop productivity and sustainability through disease identification in maize leaves: Exploiting a large dataset with an advanced vision transformer model.

Ishak Paçal

Expert Syst. Appl., March, 2024

MaxCerVixT: A novel lightweight vision transformer-based Approach for precise cervical cancer detection.

Ishak Paçal

Knowl. Based Syst., 2024

Enhancing Image Annotation With Object Tracking and Image Retrieval: A Systematic Review.

Rodrigo Fernandes, Alexandre Pessoa, Marta Salgado, Anselmo Cardoso de Paiva, Ishak Paçal, António Cunha

IEEE Access, 2024

A Deep Learning Approach to Annotating Endoscopic Capsule Videos via CBIR.

Inês Castro Fernandes, Rodrigo Fernandes, Alexandre Pessoa, Marta Salgado, Anselmo Cardoso de Paiva, Ishak Paçal, António Cunha

Proceedings of the CENTERIS 2024 - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist, 2024

2023

A comparative study of YOLO models and a transformer-based YOLOv5 model for mass detection in mammograms.

Damla Coskun, Dervis Karaboga, Alper Bastürk, Bahriye Akay, Özkan Ufuk Nalbantoglu, Serap Dogan, Ishak Paçal, Meryem Altin Karagöz

Turkish J. Electr. Eng. Comput. Sci., November, 2023

Deep learning-based approaches for robust classification of cervical cancer.

Ishak Paçal, Serhat Kiliçarslan

Neural Comput. Appl., September, 2023

Robust real-time polyp detection system design based on YOLO algorithms by optimizing activation functions and hyper-parameters with artificial bee colony (ABC).

Ahmet Karaman, Ishak Paçal, Alper Bastürk, Bahriye Akay, Özkan Ufuk Nalbantoglu, Seymanur Coskun, Omur Sahin, Dervis Karaboga

Expert Syst. Appl., July, 2023

Hyper-parameter optimization of deep learning architectures using artificial bee colony (ABC) algorithm for high performance real-time automatic colorectal cancer (CRC) polyp detection.

Ahmet Karaman, Dervis Karaboga, Ishak Paçal, Bahriye Akay, Alper Bastürk, Özkan Ufuk Nalbantoglu, Seymanur Coskun, Omur Sahin

Appl. Intell., June, 2023

Evaluation of Deep Learning Models in Search by Example using Capsule Endoscopy Images.

Rodrigo Fernandes, Alexandre Pessoa, José Nogueira, Anselmo Cardoso de Paiva, Ishak Paçal, Marta Salgado, António Cunha

Proceedings of the CENTERIS 2023 - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist, 2023

2022

Derin öğrenme tabanlı gerçek zamanlı polip tespit yöntemlerinin geliştirilmesi ve incelenmesi (Development and investigation of deep learning based real-time polyp detection methods)

Ishak Paçal

PhD thesis, 2022

An efficient real-time colonic polyp detection with YOLO algorithms trained by using negative samples and large datasets.

Ishak Paçal, Ahmet Karaman, Dervis Karaboga, Bahriye Akay, Alper Bastürk, Özkan Ufuk Nalbantoglu, Seymanur Coskun

Comput. Biol. Medicine, 2022

2021

A robust real-time deep learning based automatic polyp detection system.

Ishak Paçal, Dervis Karaboga

Comput. Biol. Medicine, 2021

2020

A comprehensive review of deep learning in colon cancer.

Ishak Paçal, Dervis Karaboga, Alper Bastürk, Bahriye Akay, Özkan Ufuk Nalbantoglu

Comput. Biol. Medicine, 2020