Brain Tumor Detection with Ensemble of Convolutional Neural Networks and Vision Transformer
| dc.contributor.author | Yurdakul, Mustafa | |
| dc.contributor.author | Tasdemir, Sakir | |
| dc.date.accessioned | 2025-01-21T16:26:36Z | |
| dc.date.available | 2025-01-21T16:26:36Z | |
| dc.date.issued | 2023 | |
| dc.department | Kırıkkale Üniversitesi | |
| dc.description | 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023 -- 27 December 2023 through 28 December 2023 -- Zarqa -- 201143 | |
| dc.description.abstract | Brain tumors are recognized as one of the most lethal cancer types worldwide. Detecting brain tumors using medical imaging techniques is a challenging task due to their complex anatomical structures. Traditional methods rely on specialists meticulously examining MRI scan images. However, this approach is not only time-consuming but also carries a significant risk of error. Therefore, there is a need for more effective methods to detect brain tumors from MRI images. In this study, an ensemble model was proposed for classifying tumor types using MRI scans. Initially, sixteen well-known Convolutional Neural Network (CNN) models and four Vision Transformer (ViT) models were trained on the Brain Tumor Dataset, which contains 3264 MRI scan images. Subsequently, by combining the top three high-performing models, we achieved a robust classification performance. Experimental results demonstrate that our proposed model provides a satisfactory performance comparedto existing methods. © 2023 IEEE. | |
| dc.identifier.doi | 10.1109/EICEEAI60672.2023.10590129 | |
| dc.identifier.isbn | 979-835037336-3 | |
| dc.identifier.scopus | 2-s2.0-85199982198 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.uri | https://doi.org/10.1109/EICEEAI60672.2023.10590129 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12587/23141 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.ispartof | 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023 | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_20241229 | |
| dc.subject | Brain Tumor; Classification; CNN; Detection; Vision Transformers | |
| dc.title | Brain Tumor Detection with Ensemble of Convolutional Neural Networks and Vision Transformer | |
| dc.type | Conference Object |
