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Data-Driven Brain Tumor Classification Using CNNs with Trainable Gabor and LoG Feature Mining Layers
Ghada Atteia,
Nabeel Ahmed Khan,
Raed Alharthi,
Abeer Aljohani,
Shtwai Alsubai,
Muhammad Umer,
Cheng Cheng 
International Journal of Computational Intelligence Systems, Volume: 19, Issue: 1
Swansea University Author:
Cheng Cheng
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© The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License.
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DOI (Published version): 10.1007/s44196-026-01281-4
Abstract
Data-Driven Brain Tumor Classification Using CNNs with Trainable Gabor and LoG Feature Mining Layers
| Published in: | International Journal of Computational Intelligence Systems |
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| ISSN: | 1875-6883 |
| Published: |
Springer Science and Business Media LLC
2026
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa71935 |
| Keywords: |
Brain tumor classification; MRI imaging; Convolutional neural networks; Enhanced gabor filters; Laplacian of gaussian; Deep learning; Medical image analysis; Interpretability; Grad-CAM; Feature extraction |
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| College: |
Faculty of Science and Engineering |
| Funders: |
Authors are funded by UKRI Grant EP/W020408/1. Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2026R748), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. |
| Issue: |
1 |