Lite-FBCN: Lightweight Fast Bilinear Convolutional Network for Brain Disease Classification from MRI Image
Achieving high accuracy with computational efficiency in brain disease classification from Magnetic Resonance Imaging (MRI) scans is challenging, particularly when both coarse and fine-grained distinctions are crucial. Current deep learning methods often struggle to balance accuracy with computatio...
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| Main Authors: | Dewinda Julianensi Rumala, Reza Fuad Rachmadi, Anggraini Dwi Sensusiati, I Ketut Eddy Purnama |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Politeknik Elektronika Negeri Surabaya
2024-12-01
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| Series: | Emitter: International Journal of Engineering Technology |
| Subjects: | |
| Online Access: | https://emitter.pens.ac.id/index.php/emitter/article/view/853 |
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