Biomedical Signal Processing and Control· 2026Q1
A controlled benchmark of CNN architectures for MRI-based brain tumor detection: Custom networks and transfer learning versus Vision Transformer baselines under a unified image-processing pipeline
- 0citations
- Q1SCImago
- 2026year
Short summary
The Vision Transformer ViT-B/16 achieved the highest accuracy (0.9665) and F1 score (0.9662) for MRI brain tumor classification, outperforming other architectures including Swin-Tiny and various CNNs under a unified processing pipeline.
AI-generated from the title and abstract; the full text is not read.
TakeawaysIn the app
Key pointsIn the app
Ask the paperIn the app
The rest is in the Pofolia app
Takeaways, key points and questions to the paper; new summaries every day for your field. Free.
Sign in on the web to openField: Neurology (Neuroscience)
NeurologyNeuroscience